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微信读书 · 神作榜

28分钟前更新
  • 01993阅读
    创伤与解离神作完结
    创伤是超越人的承受能力的痛苦。反复出现的、长期的创伤刺激会形成复杂创伤。解离是人在创伤的刺激下形成的“铠甲”。 本书从心智模型，大脑的神经生物学变化等方面深刻展现了经历复杂人际创伤的人的困境，介绍了他们在情感、记忆方面的变化，以及他们在人际关系方面出现的困难，厘清了创伤与人格发展之间的复杂关系。作者将他们丰富的临床经验提炼成了一种实用的治疗思路，提出了创伤治疗的三个阶段，并针对治疗师在实践中可能遇到的挑战提供有针对性的解决方法。 本书细腻、温暖又不失深刻，可读性极强。对于治疗师来说，这是一本实用的治疗指南。 本书适合一线的创伤治疗师和曾经历创伤的大众读者。利奈特·S. 丹尼恰克 凯文·J. 康纳斯
  • 02517阅读
    阿甘正传神作完结
    本书是经典电影《阿甘正传》小说原著。 阿甘是常人眼中的笨蛋，但他天性善良单纯，加上天赋异禀，先后成为大学橄榄球明星、越战英雄、世界级乒乓球运动员、摔跤选手、国际象棋大师和商业大亨。阿甘获得先后两任美国总统的接见和授勋，还出访中国，甚至无意间发现了水门事件的真相。[美]温斯顿·葛鲁姆
  • 031038阅读
    我的重生日记：生死之外，皆是擦伤神作完结
    【励志成长+心灵救赎+命运反击战】当原本欣欣向荣，充满希望和憧憬的年轻生命，突然遭遇无情的厄运时，他该如何接受和面对这一残酷的现实？ 作者用自己的亲身经历，记录下了这场蓬勃而感人的命运反击战。 他是不幸的，刚走出校园，准备接受向往的offer，就被确诊了再生障碍性贫血，被命运无情推向深渊。 但他又是幸运的，在与残酷疾病作战的过程中，他收获了亲情、友情和四面八方的关爱，即便在最绝望的治疗过程中，也总有温暖的光托扶着他，给他勇敢向前的力量，并最终找到希望和出路。 我们无法阻挡厄运的脚步，但没有任何东西可以夺走勇气和决心，更何况还有人心的温暖。秋树
  • 041978阅读
    半小时漫画故宫神作完结
    半小时漫画故宫其实是一本关于传统文化的百科全书，此为第一册。 陈磊（混子哥）领衔的半小时漫画团队通过诙谐的语言和手绘漫画的形式，轻轻松松地就把故宫及其背后的传统文化知识讲得清清楚楚、明明白白。故宫作为传统文化的重要载体，处处有讲究，处处皆学问： 故宫选址背后是天文历法， 故宫布局可对应八卦五行。 在三大殿了解礼仪官制， 到后三宫感受古建之美。 翻开本书，建筑、珍宝、历史、文化全看懂！陈磊·半小时漫画团队
  • 051018阅读
    窄门（加缪：圣洁与人性的永恒冲突）神作完结
    少年杰罗姆深爱表姐阿莉莎，二人一心追寻通往圣洁的窄门。在信仰与世俗情爱拉扯中彼此克制，最终遗憾别离，道尽精神修行与尘世情感的两难抉择。[法]安德烈·纪德
  • 06448阅读
    韩木洒的遗言：青海拉面人的四十年神作完结
    为什么中国的许多城市里，都有一家看起来相似的青海拉面馆？ 二十世纪八九十年代，成千上万人涌入青藏高原，在冻土、风雪与枪口之间寻找黄金。韩木洒也是其中之一。一次次出生入死后，他仍没能挖到足以改变命运的金子，最终倒在荒原深处，只给两个儿子留下一句话：“走正道，好好活着。” 父亲去世后，十三岁的韩成离开青海，跟着同乡走进拉面馆。从洗碗、揉面到站上灶台，他辗转于一座座陌生城市，寻找另一条活路。 一代人走进荒原寻找黄金，一代人走进城市守着灶火。那些遍布街巷的拉面馆里，藏着怎样的离乡往事？父亲留下的那句遗言，又会将韩成带向何处？牧风
  • 0758阅读
    发现鬼谷子神作完结
    本书作者寒川子，继其长篇历史小说《战国纵横：鬼谷子的局》之后，推出这部深度解读之作《发现鬼谷子》。如果说前者是以小说笔法演绎鬼谷子及其弟子的传奇故事，那么本书则是回归原著本身，逐篇逐句剖析《鬼谷子》这部经典的核心思想，堪称小说的最佳助读。 全书围绕“炼心立身”与“捭阖御世”两大体系展开。上篇详解《本经》《中经》的七大心术与七大践术，揭示如何通过“盛神、养志、实意”修炼内功，再以“分威、散势、转圆、损兑”等方法应用于实际，最终达到“制人而不制于人”的境界。下篇则系统梳理了《捭阖》《反应》《内揵》《抵巇》《飞箝》《忤合》等十一篇内容，将抽象的“捭阖之道”拆解为具体的“揣、摩、权、谋、决”五大实战步骤，教你如何察言观色、量权揣情、审时度势，从而在复杂的竞争与博弈中占据主动。 本书摒弃了玄奥的解读，以清晰的结构、生动的案例和直白的语言，将《鬼谷子》的智慧与现代人的职场、社交、管理等场景相结合。它不仅是一部古籍的导读手册，更是一本实用的处世方法论，帮助读者在纷繁世界中认清本质、趋利避害、成就事业。"寒川子
  • 08426阅读
    风筝（毛姆短篇小说）神作完结
    赫伯特因妻子砸毁风筝而恨透她，宁愿入狱也不付赡养费。风筝是他逃离婚姻、回归原生家庭控制的象征。[英]毛姆
  • 09343阅读
    血糖密码神作完结
    给每个人的血糖健康守护宝典，破解疾病密码、重塑健康认知。 《血糖密码》是一本写给普通人的2型糖尿病科普读物。全书以“胰岛素”为主线，系统梳理2型糖尿病的发生机制：从胰岛素抵抗的形成，到胰岛素长期过量导致的调控失灵，再到血糖逐步失控的完整链条。作者结合代谢研究与临床观察指出，传统治疗往往只关注血糖数值本身，存在治标不治本的局限，并提出2型糖尿病可以通过调整饮食结构、合理控制进食等自然手段实现预防和逆转。 在阐明原理之后，书中给出了具体的实践路径——包括日常饮食的选择与安排、循序渐进的进食方式调整等，步骤清晰，落到日常可执行的细节；同时，作者也强调这些调整应在专业医疗人员的指导下进行。对于希望了解2型糖尿病成因、或希望通过生活方式管理血糖的读者，《血糖密码》提供了一份清晰、可操作的参考。[加]杰森·冯著 孙璐译
  • 10183阅读
    信（毛姆短篇小说）神作完结
    英属马来亚，种植园主夫人枪杀友人，坚称自卫。一封勒索信浮出水面，揭开婚外情与蓄意谋杀的真相，尽显人性的虚伪与冷酷。[英]毛姆
  • 11449阅读
    肥皂(鲁迅短篇小说)神作完结
    道学先生四铭买回一块肥皂，借议论街头孝女，在家中大谈礼教。鲁迅以细腻笔触，撕开旧式文人表面恪守道德，内心虚伪龌龊的真实面目。鲁迅
  • 12164阅读
    禅者的初心（果麦经典）神作完结
    铃木俊隆是用禅学影响西方人的宗师，这本书作为举世公认的禅学入门读物，英文版已畅销50多年，是苹果创始人乔布斯学禅的入门书。 本书鼓励读者活出自己，探索新生，通过修行来了悟自己的本心真性。 禅修在全世界的流行，在于能解决人们遇到的日常困惑，助人修身养性、减轻压力、充实生活、开显智慧，在树立人生观、世界观等方面都有积极作用。[日]铃木俊隆
  • 13229阅读
    一半命运设定，一半我来决定神作完结
    从人生理想2000元月薪的普通女孩，到全球100强企业的管理培训生；从前途一片光明的公司高管，到陪伴早产女儿康复的全职妈妈；从需要他人给予力量的求助者，到给无数家庭带去希望的早产儿公益项目发起人，命运不断给大J设置难题，她却用 “傻傻的”坚持，重新主导了自己的人生。 在普通院校“起点不够好，期待别太高”的氛围里，她坚持去找别人看作是“打杂”的实习工作，为自己积累出亮眼的实习经验，开启了职场的顺风之路。 在早产女儿被诊断成脑瘫高危儿时，她内心笃定，努力学习护理知识，专注于女儿每一次的康复训练，从不质疑付出是否有回报，用一千多个日夜的陪伴，创造了医学界的一个奇迹。 在创业的风口不断变化时，她坚持打磨自己的专业能力，相信自己的“硬指标”才是核心竞争力，逐步成长为500万粉丝信赖的亲子教育博主。 这是真实的大J和她真实的故事。接受命运的设定，她的人生变得松弛，努力逆袭破局，她一路收获成长，把命运给的“烂牌”变成了自己的“王牌”。大J
  • 14244阅读
    妻子（契诃夫短篇小说）神作完结
    契诃夫短篇小说《妻子》的主人公巴威尔·安德烈耶维奇是一位退居乡村、撰写《铁路史》的知识分子。他收到求助信，得知附近村庄的农民因饥荒和伤寒陷入绝境，而地方自治局拒绝赈济。与此同时，他与妻子娜达丽雅·加甫利洛芙娜关系疏离，她住在楼下，对他的理想和社会关切漠不关心。小说通过这一双重困境，深刻刻画了知识分子的精神无力与庸俗自私。[俄]契诃夫
  • 15127阅读
    上校夫人（毛姆短篇小说）神作完结
    人人都读《面纱》《月亮与六便士》，却很少有人发现毛姆最锋利的婚姻短篇 ——《上校夫人》 刻板上校一直认定妻子平淡无趣，直至她匿名诗集轰动文坛。丈夫细读诗篇，才窥见妻子深藏多年的炽热秘恋。直面婚姻表层体面之下的巨大隔阂。[英]毛姆
  • 16159阅读
    格特露德神作完结
    《格特露德》是德国作家，诺贝尔文学奖得主赫尔曼·黑塞的“艺术家小说”之一，塑造了性格截然不同的两个人物：歌剧演员摩特和腿有残疾的作曲家库恩，个人主义者摩特必须为满足观众盲目而狂躁的激情，换取名誉与金钱，但他又厌恶这一切，因此内心孤寂而虚空，最终在绝望中自杀。库恩年少气盛，滑雪摔断了腿，从此丧失了青春的欢乐，他将自己的全部生命力倾注到对艺术的完美追求上，获得了事业的成功，但在感情上因怯懦酿成终生遗憾。[德]赫尔曼·黑塞
  • 17132阅读
    海瑞当官：大明王朝第一清官神作完结
    1558年的一个倒春寒日，海瑞拖家带口，自己赶着牛车去赴新任。 在此之前，海瑞被分配至福建南平县任教谕，但很快他就以宁折不弯的“海笔架”绰号而闻名远近，受到官场排挤，正欲弃官归田之际，又鬼使神差地得到了淳安县知县的任命。 就这样，来自海南的海瑞初次当官，成了大明王廷最基层的一个芝麻官，也成了淳安县百姓头顶的一片天。面对淳安县生活困苦的人民、并不服上的下属、暗中与倭寇勾结的官员以及纷纷扰扰扯不断丢不掉的琐碎家事，海瑞冷静睿智，以超常的胆识和智慧，于不动声色中一一破解，使有罪者伏法，使无辜者迎来公义，使家庭关系重归和谐，使淳县吏治焕然一新，使辖域生民安居乐业。 本书以一桩通天冤案为主轴，将有趣的文风与海瑞的正经人设相结合，详细讲述了大明王朝第一清官海瑞初次踏入仕途，冲破层层压力、智断铁案、惩恶扬善的一段传奇故事。寒川子
  • 18229阅读
    中国：全三册神作完结
    大型人文历史纪录片《中国》官方同名书，第31届中国电视金鹰奖最佳纪录片奖。一部可以朗诵的历史，一场跨越千年的华夏文明寻根之旅。 上册对应纪录片第三季，自盘古创世、上古神话开篇，梳理史前邦国、夏商文明，止于西周礼乐，探寻文明最初的根脉；中册对应纪录片第一季，从春秋战国诸子百家讲起，历经秦汉大一统、魏晋民族交融，直至大唐盛世，再现思想黄金时代与王朝风华；下册对应纪录片第二季，承接盛唐之后，叙写宋元明清的王朝更迭，一路讲述至辛亥革命，见证古典文明走向近代的漫长历程。 丛书完整收录纪录片原版解说词，搭配数百幅高清文物实拍、山河风光与历史剧照，全彩印刷，图文互映。以人物与思想为线索，跳出碎片化历史知识点，娓娓讲述华夏文明生生不息的故事，读懂中国人的精神源头与文明底色，是一套兼具文学美感、史料价值与收藏价值的人文典藏读物。纪录片《中国》创作组
  • 19271阅读
    朝花夕拾：鲁迅散文集神作完结
    为了纪念鲁迅小说《祝福》发表100周年，获北京鲁迅博物馆授权，本次推出“我的沉默震耳欲聋”鲁迅作品精选系列（包含小说、散文、杂文、传记）插画本，shou度收入鲁迅藏木刻版画、鲁迅照片等珍贵影像。 《朝花夕拾：鲁迅散文全集》是“我的沉默震耳欲聋”鲁迅作品精选系列之中的散文插图本。其中《朝花夕拾》（1926）共10篇，《野草》（1927）共23篇，《两地书》（1934）共3集，本书中所精选收录的各篇散文，参校1936年版《鲁迅全集》（di一版）及人民文学出版社2005年11月版《鲁迅全集》等版本编辑而成。为z大程度上保留原作精髓，全书的通假字和鲁迅习惯用字，仍完全保留。另有外国人名、地名等，亦均保留原有译法，不作修改。同时为方便阅读，对书中的人名、地名、作品、重要事件等进行必要注释。鲁迅
  • 20127阅读
    消失的地平线神作完结
    一架偏离航线的小型飞机坠落在青藏高原的雪原，四位乘客被带入神秘的香格里拉山谷。 这个传说中的乌托邦究竟是劫持者的巢穴，还是命运馈赠的避世桃源？英国领事康威在香格里拉经历了超越世俗的体验，面对重返文明世界与永留理想之地的抉择。 小说以沉静的笔触描绘了人类对乌托邦的永恒追寻，其谜团般的结局至今仍引发无数解读。[英]詹姆斯·希尔顿
今日全部20条查看完整榜单

arXiv · eess.SY

17分钟前更新
  • 01
    Distributed Global Pose Synchronization for Heterogeneous Multiple Rigid Body Systems on SE(3)
    This paper addresses the problem of global pose synchronization for heterogeneous multiple rigid-body systems evolving on the matrix Lie group $\SE(3)$. We first construct a new potential function on $\SE(3) \times \mathbb{R}$ with a generalized non-diagonal weighting matrix, together with a set of switching variables governed by continuous-discrete hybrid dynamics. Based on this new potential function and these switching variables, we propose a distributed hybrid feedback control scheme that usFengyu Lin
  • 02
    Safe Performance-aware Online Input Design
    In this paper, we propose an input design framework for the safe online excitation and identification of uncertain linear systems without requiring informative initial data. The objective is to actively excite the system and collect sufficiently informative input-output data while maintaining safe operation and satisfactory control performance. Achieving this objective is challenging due to the potential conflict between the excitation required for learning and the safety and performance requireDiyou Liu
  • 03
    Certified Zonotopic Reachability Analysis for Trajectory Tracking on Lie Groups
    Autonomous vehicles track planned trajectories close to obstacles. Unknown disturbances make them deviate from these trajectories. With a bound on the tracking error that disturbances can cause, a planned trajectory can be certified as safe before execution. Existing set-based methods bound the tracking error by one invariant ellipsoid for the whole trajectory or by intervals, which are both conservative. For aerial and space vehicles, the tracking error evolves on a matrix Lie group with nonlinYanliang Huang
  • 04
    Succinct Infinite-Horizon Lyapunov and LQR Value Problems Are BQP-Complete
    Fundamental tasks in linear systems analysis and control require evaluating infinite-horizon output energies for autonomous systems and optimal value functions for controlled systems. These quantities are characterized by Lyapunov and algebraic Riccati equations, respectively. In this work, we study promise problems for their evaluation when the system matrices are sparse and represented succinctly by Boolean circuits specifying their nonzero entries, with input length polynomial in the logarithMohamed Serry
  • 05
    Sliding into Balance: Benefits of a Sliding Payload for Load Distribution and Disturbance Rejection in Dual-UAV Transportation
    This paper analyzes the cooperative transportation of a payload suspended from two drones in which, instead of being attached to two independent ropes, the payload is allowed to slide along a single rope connecting both UAVs. First, a planar nondimensional dynamical model of the sliding motion with viscous friction is presented. Then, considering stationary drones, this configuration is compared with a fixed payload with the same total rope length, both at equilibrium and under disturbances. TheJorge Vicente-Martinez
  • 06
    KL-Regularized Policy Iteration for Adaptive LQR: Gain Updates and Probing from One Policy Improvement
    Policy-gradient methods for adaptive linear quadratic control improve the feedback gain of an unknown plant online by gradient-type steps computed from closed-loop data. A recent framework of such methods, policy-gradient adaptive control (PGAC), takes one gradient-type step per sample, which its indirect form computes from an estimated model and its direct form directly from the data. Because data generated by a fixed linear feedback cannot identify the plant, PGAC adds a probing perturbation tAjinkya Bhole
  • 07
    Hierarchical Nonlinear Control for Swarm Encirclement Around a Moving Target UAV
    This paper presents a hierarchical inner-outer loop nonlinear control strategy using a geometric Lyapunov-based framework for the cooperative encirclement of a target by multi-ple unmanned aerial vehicles (UAVs) in three-dimensional space. The encirclement problem is formulated on a two-sphere with arbitrary radius and center, denoted Gamma-2, by projecting agent positions from R3 onto a spherical manifold centered at the target, being the unit two-sphere at the origin S2 used for intermediate cFilipe S. Cavalheiro
  • 08
    Offset-Free Data-Driven Predictive Control: Implicit and Explicit Disturbance Formulations
    Offset-free tracking is a key objective of any control algorithm. For predictive controllers with linear models, it is well understood that rejecting asymptotically-constant disturbances necessitates augmenting the prediction model with $p$ integrating states, where $p$ is the number of measured outputs. This can be achieved in model predictive control (MPC) by using a velocity form or a combination of disturbance model and observer. In data-driven predictive control (DPC), implicit incorporatioLucca Heinze Faro
  • 09
    Reshaping Checkpoint-Induced Power Variations Through Inference Workload Scheduling
    Synchronous checkpoints in large language model training cause rapid power variations that challenge frequency regulation in islanded data-center microgrids. This paper proposes a checkpoint-aware two-layer framework that schedules flexible inference workloads to compensate for checkpoint-induced disturbances. Using measured GPU power profiles and anticipated checkpoint power deficits, the upper layer coordinates heterogeneous task selection and launch times, while the lower layer adjusts the baYu Ma
  • 10
    Converse Lyapunov theorem for input-to-state stability of infinite-dimensional systems
    We prove converse Lyapunov theorems for input-to-state stability (ISS) of a broad class of infinite-dimensional systems applicable to evolution equations in Banach spaces, boundary control systems, and delay systems. To this end, we employ a novel method that does not require constructing auxiliary closed-loop systems. We start by showing that ISS of a control system implies uniform global asymptotic stability of the same system with respect to trajectory-dominated inputs. Then, under an additioPatrick Bachmann
  • 11
    Covert System Identification Under Timing Constraints: A Static Linear Model and Its Detectability Implications
    This paper studies covert system identification in cyber-physical systems, where an attacker infers plant dynamics while attempting to remain stealthy. We introduce a lightweight static linear model in which the time to execute a setpoint change is proportional to the commanded speed difference. On a Siemens PROFINET testbed this gain captures the drive's ramp response accurately but not its terminal overshoot. That omitted transient becomes the attacker's main exposure: on real traces, the resiVictor Mattos
  • 12
    Degradation-Aware Participation of Battery Storage in Frequency Regulation Markets
    As data centers make the load on the power grid fluctuate faster, frequency regulation grows more valuable. Battery energy storage systems (BESSs) are well suited to provide frequency regulation, but providing this service speeds up aging, especially during operation at extreme state of charge (SoC). In the PJM interconnection, the grid operator supplies a regulation signal that a participating BESS is expected to follow, within a capacity that it must bid before the signal is known. AccordinglyAnand Gokhale
  • 13
    Towards Passivity-informed Data-driven Predictive Control
    We propose a passivity-informed data-driven predictive control framework based on passivity-preserving sampling of unknown continuous-time linear systems. We incorporate the passive supply rate into the objective functional alongside an output-regulation cost, thereby explicitly accounting for energy extraction. Despite being practically motivated, the resulting objective is not always convex; its convexity depends on the collected input-output training data. We exploit passivity-induced positivGuanru Pan
  • 14
    KPG193-ext: A Synthetic Korean Power Grid Test System for Stability Analysis
    Growing shares of inverter-based generation and constrained transmission expansion increase the need to assess stability across operating conditions. Production-cost models provide chronological commitment and dispatch, but stability analysis requires corresponding electrical detail and device dynamics. This paper introduces KPG193-ext, an extension of the synthetic Korean power-grid test system KPG193 that links chronological operating points with detailed electrical and dynamic models. The extSungyoon Song
  • 15
    Scalable Practical Synchronization of Heterogeneous Linear Systems
    We study practical state synchronization of heterogeneous linear multi-agent systems over directed graphs using static diffusive state feedback. Persistent mismatches between the agent dynamics generally preclude exact synchronization and are treated as bounded disturbances within an Input-to-State Stability (ISS) framework. We derive a scalable synthesis procedure based on fixed-dimension linear matrix inequalities (LMIs), whose dimension is independent of the number of agents. Local robust disAlex Ardelean
  • 16
    Sensor placement for real-life water distribution networks, ensuring observability under uncertainties
    Leakage detection in water distribution networks (WDNs) is crucial for limiting water losses. However, effective detection strongly depends on sensor availability and placement. Most existing sensor placement methods rely on extensive simulations or precise knowledge of hydraulic parameters, which are often uncertain in practice. In this paper, we propose using a scalable sensor placement framework based on structural observability that depends only on the network topology and the underlying preJarne J. H. van Gemert
  • 17
    Observer-based parameter estimation in a Darcy model towards dam internal seepage monitoring with validation on real data
    This paper addresses internal seepage monitoring in hydraulic infrastructures through the estimation of physical parameters in a distributed model. A physics-based approach relying on Darcy's law is adopted to describe the spatiotemporal evolution of hydraulic head within the structure. To enable real-time applicability, a Proper Orthogonal Decomposition (POD) is employed to derive a reduced-order model of the underlying partial differential equation. An Extended Kalman Filter (EKF) is then desiAndrea Ferretti
  • 18
    Safety-Constrained Intelligent Control of a 2-DOF Robotic Manipulator Using Control Barrier Functions
    Control barrier function (CBF) filters depend on dynamic models that can be inaccurate when their parameters and external forces are uncertain. This paper investigates a radial basis function (RBF) neural network compensator whose output is shared by a Cartesian tracking controller and a joint-space CBF filter. An auxiliary state driven by the difference between requested and applied torques corrects the learning signal, reducing the direct influence of filter intervention on adaptation. A two-lGabriel da Silva Lima
  • 19
    Tensor Network Kernel Machines for Nonlinear System Identification
    Over the past ten years Tensor Network Kernel Machines have enabled efficient nonlinear system identification through the use of low-rank tensor networks. The goal of this article is to provide the reader with a basic understanding of this model class in terms of its two defining properties. Furthermore, both the optimization and regularization of such models are discussed, together with recent developments and starting points for further exploration.Kim Batselier
  • 20
    A Scale-Space Theory of Memory
    Scale-space theory has emerged as a central attempt to restrict the {\it general} theory of signal processing with geometric constraints inspired from the animal world. In the mathematical language of operator theory, scale-space theory restricts the Toeplitz operator. The present paper investigates scale-space theory for memory systems. We investigate how scale space theory restricts a memory system encoding past information, that is, restricts the Hankel operator. Our main result is to establiDongjun Wu
  • 21
    Prospective Action-Resource Graph Multi-Agent Reinforcement Learning for Electric HGV Fleets under Shared Charging Infrastructure
    Electric heavy goods vehicle (eHGV) fleet coordination requires each vehicle to choose driving, charging and resting actions whose consequences depend on shared infrastructure. Existing multi-agent reinforcement learning (MARL) methods mainly represent current states, leaving action-specific futures and resource interactions to be learned indirectly. We develop Horizon-Preview and Graph-Coordinated Proximal Policy Optimisation (HGC-PPO), which integrates horizon preview and candidate-resource grYiming Xu
  • 22
    A Game-Theoretic MPC Planner for Cooperative and Adversarial Drone Coordination
    We present and evaluate a game-theoretic model predictive control planner for cooperative goal reaching and adversarial pursuit-evasion with drones. The planner combines 3D prediction, individual objectives, optional shared separation constraints and trajectory-tracking interfaces. A comparison of cooperative game solvers assesses their ability to find feasible trajectories that resolve conflicts. A computational study quantifies how number of drones, prediction horizon and move blocking affectZdeněk Bouček
  • 23
    Environmental Assessment of GaN Current-Source and Voltage-Source AC-AC Variable Speed Drives
    Three-phase ac-ac converters for variable-speed drives can be realized conventionally as voltage-source converters (VSCs) or, leveraging emerging monolithic bidirectional GaN power transistors (M-BDSs), as current-source converters (CSCs). This paper presents a comparative life-cycle assessment of a realized VSC and a CSC demonstrators including grid-side and motor-side EMI filters, and with identical specifications (1.4 kW rated power, 200 V line-to-line rms grid and motor voltage). The embodieLuc Imperiali
  • 24
    DC Voltage Control Dominated Oscillations in Electromechanical Frequency Range - Insights from Synchronous Coefficient Reduction Effect of IBR Plants and Network Interactions
    Large-scale integration of inverter-based resources (IBRs) is widely known to cause subsynchronous oscillations. This paper investigates a distinct class of oscillations that occur in the electromechanical frequency range (EFR), referred to as EFOs, and are dominated by the DC voltage control (DVC) loops of grid-following IBRs rather than synchronous generator-like controls or phase-locked loops (PLLs). Although open-loop oscillation modes of DVC loops are subsynchronous, the corresponding closeQiang Fu
  • 25
    On necessary conditions for feedback stabilizability when the control space is a fiber bundle
    Within control theory, a question of great interest is to understand when a stabilizing feedback exists. Building upon Krasnosel'skiĭ and co-workers, necessary conditions for the existence of a continuous stabilizing feedback have been pioneered by Brockett and Coron, providing so-called adversarial and homological conditions, respectively. Kvalheim recently generalized their conditions from equilibria to compact attractors and---in line with earlier work by Coron---showed that when a control syWouter Jongeneel
  • 26
    Compact and Wide-Force-Range Magnetorheological Hand Exoskeleton for Kinesthetic Feedback in Teleoperation
    Hand kinesthetic feedback is crucial for restoring and enhancing human perception of force and displacement in robotic hand teleoperation. Wide perception range of force feedback is vital in rendering objects of different stiffness, especially for high-stiffness rendering. However, existing approaches struggle to achieve wide range of force feedback while maintaining compact and wearable design. This paper presents a hand exoskeleton system employing magnetorheological (MR) brakes to provide a wXianlong Mai
  • 27
    One number per hour is not enough: directional carbon intensity of data-center ramps on the PJM fleet
    A data-center campus can change its load by hundreds of megawatts within an hour, yet every carbon signal in use gives one value per hour for a load change, whatever its size or direction. We compute the directional carbon intensity, the emission caused or avoided per megawatt-hour of a finite upward or downward ramp, for every hour of 2025 on the PJM Interconnection's fossil fleet, and compare it with the locational marginal emission rate (LME) and the regional average. The LME misstates a 1 GWXiaoying Shi
  • 28
    Online Digital Twins: Data Assimilation and Control
    The online assimilation of data and the application of controls are essential ingredients of the digital twin paradigm. In this paper, we formalize the online interaction between the physical process and its virtual digital representation in the setting of continuously arriving data from the physical process and a receding horizon virtual planning process, which provides the control for the physical process. Our mathematical formulation relies on a mean field representation of the data assimilatSebastian Reich
  • 29
    Generalizable Output Feedback Optimal Control via Transformers Without Explicit State Estimation
    Classical optimal control is used to design a separate controller for each plant. This paper asks a different question. Can one learned policy serve a whole family of partially observed, noisy linear systems? We show that one transformer can. The policy is trained to imitate optimal LQG control on a heterogeneous family of Linear Time-Invariant (LTI) systems with Multiple Inputs and Multiple Outputs (MIMO), whose dimensions, cost matrices, and noise levels all vary. A shared representation withMaitham F. AL-Sunni
  • 30
    MAC+: Mobility-Aware Co-Expansion Planning for Distribution Grid and Electric Vehicle Charging Infrastructure
    We study the least-cost co-expansion of power distribution networks and public charging ports to accommodate the growth of electric vehicles (EVs). Our approach, MAC+, exploits the flexibility of charging along each EV's itinerary and coordinates it across the fleet to reduce the peak violations of each feeder's hosting capacity and port capacity. This coordination is an extremely large, spatio-temporally coupled optimization problem with binary plug-in variables. We solve it by iterated price rYi Ju
  • 31
    Graph-Sparse Distributed Predictive Control for Multi-Robot Motion Planning vianEdge-Consensus ADMM
    This paper presents a distributed model predictive control (MPC) architecture for collision-avoiding motion planning of planar robots with double-integrator dynamics. To reduce coordination demands, a time-varying predicted conflict graph selects relevant pairwise interactions. The associated collision-avoidance constraints are convexified once per MPC update using warm-start trajectories, yielding a fixed convex quadratic program (QP). The resulting QP is then decomposed using an edge-consensusJosep Borras-Borras
  • 32
    Silinx: An Open, Browser-Based HDL Design Platform for Teaching Digital Systems on FPGA Boards
    Many digital systems courses teach on FPGA boards whose vendor tool is no longer maintained: the Digilent Basys2 and Nexys2 (Xilinx Spartan-3E) and Nexys3 and Atlys (Spartan-6) need Xilinx ISE 14.7, discontinued since 2013 and hard to install on the computers and tablets students use today. The author presents Silinx, a free (AGPL-3.0) HDL design platform for teaching that keeps ISE's Project Navigator workflow but runs in a web browser with nothing to install. A module can be written in VHDL orPedro Malo
  • 33
    A Bifurcation-Theoretic Framework for the Controllability of Emergent Intelligent Systems
    Real-world intelligent systems must reconcile two demands: the adaptability conferred by emergence and the steerability required for accountable deployment. We show that these demands are governed by two distinct bifurcations on the same object and that, consequently, increased capability does not imply increased controllability. Emergence is a bifurcation of the capability variable $S$, with criterion $Γ:=\mathcal F'(0)>1$ equivalent to the existence of a unique positive stable fixed point of aHao Li
  • 34
    Scarcity Pricing for State-of-Charge Management in Real-Time Markets Under Intra-Day Uncertainty
    The growth in renewable resources will increase net load variability and forecast error. Energy storage resources can provide flexibility when ramp capability is limited and contribute to load leveling over the day. The challenge for system operators is how to balance these two functions in real time, when updated net load forecasts are available for a limited lookahead horizon. U.S. electricity markets are seeking ways to manage state-of-charge (SoC) within their energy markets to more efficienShailesh Wasti
  • 35
    ShadowBench-MCP: Measuring Shadow Invocations in MCP-Style Tool Routing
    LLM agents increasingly act as routers for tools, APIs, and software-supply-chain workflows, making an execution path - rather than generated text alone - a security-relevant model output. We study shadow invocation: a task-preserving request variant that causes an LLM router to select a riskier execution path, potentially skipping validation, provenance, staging, redaction, or audit controls even though the request does not ask for a malicious action. We introduce ShadowBench-MCP, a benchmark aEyhab Al-Masri
  • 36
    Rapid Heat Removal from Chip Cores: Near-Junction Active Cooling of Power Transistors via Electron Entropy Transport and Spatial Decoupling
    Chip performance is limited by a shared bottleneck: the core produces heat faster than it can be moved out. We study the hardest case, RF power GaN HEMTs, whose hotspots exceed 5 kW/cm^2, and propose a horizontal near-junction active cooling topology built on electron entropy transport. Classical on-chip thermoelectric cooling faces a contest: Peltier absorption grows linearly with current, Joule heating with its square. In a vertical pillar, its own conduction resistance locks about half the JoXiangying Li
  • 37
    PA-SaR: Perception-Aware Learning, Control, and Coordination for Multi-Robot Search and Rescue
    Autonomous SaR requires robots to explore unknown or partially known environments, avoid hazards, coordinate team activities, and guide discovered victims to safety. Improving individual capabilities of robots does not necessarily improve mission outcomes: safer motion can restrict the exploration behavior, faster discovery can increase the rescue demand, and effective guidance depends on victim responses. We introduce PA-SaR, a mathematical and architectural framework for coordinating heterogenJocubas Dimsa
  • 38
    Predictive Neuromorphic Control of a Scanning Mirror System: An Event-Centric Framework
    Organizing control around events can reduce sensing and actuation demands while directly linking control decisions to the occurrence and timing of desired system behaviors. This paper proposes a novel event-centric model predictive control (MPC) framework that unifies event sensing, event prediction, and event regulation. Events define the feedback information, prediction horizon, and event-timing objectives, placing them at the center of predictive control design. The framework is developed forChangrui Liu
  • 39
    Concurrent Learning-Based Inertial Parameter Estimation and Control of Quadrotors
    In this letter, we consider trajectory tracking control and inertial parameter estimation of a quadrotor UAV whose center of mass (CoM) does not coincide with its geometric center. Onboard payloads like an IMU, a camera, or a battery are not necessarily placed at its geometric center. Moreover, during the flight these sensors might move because of external disturbances and cause a CoM offset. Thus, these events and equipment introduce an offset and cause the inertia matrix to be non-diagonal. WeSandesh Thapa
  • 40
    Ultrawideband Polarization-Rotating Antenna for Enhanced Ground Penetrating Radar Detection
    Ground penetrating radar (GPR) represents a powerful and widely adopted tool for nondestructive subsurface detection and imaging. To overcome the impaired detection performance caused by polarization mismatch in conventional single-channel GPR systems, this paper presents an innovative ultrawideband polarization-rotating (UPR) antenna that achieves rotating linear polarizations (LPs) by varying the source frequency for enhanced detection. The developed UPR antenna achieves a continuous polarizatMing Li
  • 41
    K-PWM: Control-Oriented Structured Bilinear World Models under Partial Observation
    World models learn internal simulators of environment dynamics for prediction, planning, and control, yet learning them from limited, noisy, and partial observations remains challenging. While much progress has focused on pixel-based observations, many physical systems instead provide vector-valued measurements that reveal only part of the underlying state. We introduce K-PWM, a probabilistic world model for prediction and control under partial observation. K-PWM couples Koopman-bilinear latentSantosh Mohan Rajkumar
  • 42
    Local Certificate Repair for Asynchronous Controller Updates in Recommender Systems
    We study how to adapt an existing distributed recommendation controller when local dynamics or objective weights change. Starting from a quadratic stability and cost certificate, we construct positive semidefinite corrections with finite spatial support and an explicit residual. A joint admission test allocates the available dissipation margin to these residuals and to interactions among changes and corrections, including pending updates. The test covers complete declared parameter ranges, allowSimone Mariano
  • 43
    A Distributed Observer with Random Agent Activations over Random Communication Networks
    This paper develops a distributed observer for the forward-Euler discretization of a continuous-time linear time-invariant system under random local operations and random communications. Under uniform stochastic strong connectivity, we establish almost sure exponential convergence of all local state estimates for sufficiently small discretization step sizes. We further examine how the underlying parameters and components affect the admissible range of the discretization step size and the guarantYong Joo Do
  • 44
    Scenario-Based Assessment of Transport Electrification for Low-Carbon Urban Planning: A Case Study of Phu Quoc, Vietnam
    Urban net-zero strategies require a defensible emissions boundary and quantitative estimates of the contribution achievable through individual mitigation measures. This study assesses road-transport electrification within a planned residential development in Phu Quoc, Vietnam, using the assumptions and scenario data of an urban-planning study originally prepared in 2022. A vehicle-class inventory combines population-dependent fleet projections, assumed travel activity, gasoline and diesel consumTien-Khai Nguyen
  • 45
    GFM Control Automatic Compliance Toolbox
    The increasing penetration of converter-interfaced generation reduces system inertia, short-circuit strength, and voltage support. European grid codes, including the ENTSO-E Network Code on Requirements for Generators and the ACER Demand Connection Code, now define disturbance-based validation procedures for grid-forming (GFM) generation and converter-based demand. Commercial RMS tools, however, lack an integrated workflow aligned with these recent requirements. This paper presents an automatedTejas Kunbi
  • 46
    Grid-forming Control of Offshore Wind through a Diode-Rectifier HVDC System: a 2 GW Case Study
    Diode-rectifier-unit (DRU)-based high-voltage direct current (HVDC) transmission considerably reduces the volume and weight of the offshore converter platform for remote wind farms and, hence, its cost, but shifts the task of forming and regulating the offshore AC network to the wind-turbine converters. This paper examines which grid-forming control strategy is the most suitable for DRU power transfer. The DRU commutation relationship shows that the delivered active power depends on the offshoreIshi Nigam
  • 47
    Spot Markets for AI Inference: Dynamic Capacity Allocation and Pricing on a Shared Accelerator Fleet
    Inference providers size their accelerator fleets for the interactive peak and sell spare capacity through fixed discounts, such as batch tiers at half price. However, inference differs from conventional cloud capacity in four respects: capacity depends on the latency tier through batching, moving weights between models is slow and costly, spot demand can wait until its deadline, and power can bind. In this paper, we develop a framework for dynamic capacity allocation and pricing of AI inferenceQuanyan Zhu
  • 48
    A Multistage Extension of Witsenhausen's Counterexample with Linear Signaling
    We study a multistage scalar extension of Witsenhausen's counterexample in which controller 1 observes the initial state exactly, whereas every subsequent controller observes only a local noise-corrupted state and does not inherit its predecessors' observations, so that every nonterminal action both regulates the state and shapes the signal available to the next controller. Restricting the signaling controllers to linear policies while leaving the terminal controller unrestricted, we compute theQuanyan Zhu
  • 49
    Numerical Stability Issues and a Mitigation Method in Switching Events Calculation Considering State Variable Discontinuities for EMT Simulation
    Some existing methods for switching events calculation considering state variable discontinuities for EMT simulation can encounter numerical stability issues, either over-stabilizing or destabilizing the studied power systems. This paper documents these issues in detail with a concrete example. The underlying mechanism of the issues are revealed via systematic analysis. A mitigation method for the issues is proposed. The convergence behavior of the method is analyzed. Numerical examples demonstrSheng Lei
  • 50
    Learning the NMPC with Stability Guarantees
    Although nonlinear model predictive control (NMPC) is widely used, its online optimization is computationally expensive. Neural network approximations of NMPC can effectively reduce the online computational burden but generally lack stability guarantees. This paper proposes an approximate NMPC framework with guarantees of constraint satisfaction and closed-loop stability. The approximation error is addressed through constraint tightening, and the resulting tightened NMPC is used to generate theShuyou Yu
  • 51
    Analysis increments for model bias diagnosis and correction: Theoretical foundations
    A common method for diagnosing and correcting model bias in weather and climate prediction is based on analysis increments: the difference between the analysis and the forecast at each data assimilation cycle. Their time average is used to estimate and correct the bias, and machine learning is increasingly used to map the forecast state to the increments, giving a state-dependent correction. Despite its widespread use, the method lacks theoretical foundations. We first analyse a Kalman filter whEviatar Bach
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  • 01
    十年磨一剑 筑牢基础软件底座
    十年前，中国科学院软件研究所组建RISC-V基础软件团队。如今，国内RISC-V生态实现了从“有芯片可用”到“有软件可跑”，再到“生态有人共建”的阶段性跨越。樊晓丽，张欢
  • 02
    分类改革后，应用型高校如何定义自己
    应用型高校不再是“没够上‘双一流’的研究型大学”，也不是“拔高版的高职院校”，它们必须重新定义自己，重新回答我是谁、我为谁存在、我凭什么被需要。侯志军
今日全部2条查看完整榜单
  • 0198阅读
    死者(九读 · 一天读完一本经典）神作潜力完结
    以一夜落雪，照见人世间的孤独与温柔。 冬夜，一场温情与虚饰交织的聚会上，加布里埃尔在体面与礼节中周旋，沉浸在对生活了然于心的自信中。直到聚会散去，妻子格蕾塔的一段旧情回忆让他第一次感到内心的荒芜，并看见爱情与生命的深度。 窗外，“整个爱尔兰都在下雪……轻轻地落在所有生者与死者的身上。”[爱尔兰]詹姆斯·乔伊斯
  • 02781阅读
    海昏疑云（微信读书特别版）神作潜力完结
    读史就是读人性——所谓料事如神，实际上都是料人如神。 江西南昌有一座西汉大墓，从中出土了115公斤金器、十余吨五铢钱、失传1800年的《齐论语》、以及现存最早的孔子画像。 墓的主人叫刘贺。他是汉武帝的孙子，七岁当昌邑王，十九岁被立为天子，在位仅27天就被废黜，弹劾书说他27天干下1127桩荒唐事，他的继任者就是后来的汉宣帝。此后11年，刘贺身份不明，三十四岁去世时他的头衔是海昏侯。 十五岁的太后，六十岁的权臣，昭宣之治的离奇过渡，支离破碎的正史记载，一盘大棋若隐若现。读史就是读人性，易中天带你细读史料，重新梳理时间线，画人物关系图，参考前辈学人成果，代入人物排查动机，大胆假设仔细推敲，破解这桩两千年前的悬案。易中天
  • 0353阅读
    当我们比光还轻神作潜力完结
    百万畅销书《橘子不是惟一的水果》作者关于宇宙与爱情的神谕之书！ 没有哪个男人，值得你丢掉自己！一位物理学家，一位诗人，在同一个男人的引力场中相遇，却被彼此深深吸引。小说以一段如粒子般纠缠的三角恋，剖开女性在爱中的迷失与觉醒。温特森掷下箴言：“在一个女人想厘清自己、开启人生的时候，男人真的太占地方了。” 如果是时间是一条可以弯曲的河，宇宙是一个不断膨胀的谜团，那么自我、身份的边界也可以具有弹性。 这个故事关乎寻找，也关乎松动。 松动那些被嵌进脊椎、嵌进姓氏、嵌进“你应该成为谁”的古老戒律。 当塔罗牌翻开，钻石之光闪动，愚人船终于启航，你会发现： 引力可以束缚肉身，但在相爱的时刻，我们比光还轻。[英]珍妮特·温特森
  • 04166阅读
    意大利蠢事集神作潜力完结
    汇集50篇短篇小说。蒙塔莱从童年写起，回忆曾经珍重的人与事，在个人记忆中映照出二战前后意大利的文化与政治图景。家人、朋友、动物、物件；难忘的邂逅、啼笑皆非的经历……一切都曾真实而鲜活地存在于蒙塔莱的生命中。它们此刻如同善解人意的幽灵，守候在故事的每个角落，陪伴作者一同穿越记忆的迷雾。[意]埃乌杰尼奥·蒙塔莱
  • 05143阅读
    恶魔召唤（全球直播求生游戏）神作潜力完结
    “玩游戏吗？要命的那种——” 三年前，代号“潜行者”的年轻人倒在撒旦游戏的最后一关。 全球直播里，他被三名玩家联手伏击，全世界看着他死去，又很快把他遗忘。 三年后，他的姐姐接过编号7的黑卡，成为第七名玩家。代号：战士。 她叫闻声。她走到这里只有一个理由：撒旦能实现任何愿望，哪怕是让一个死了三年的人重新睁眼。 雨林、沙漠、海岛、冰川、地宫、废土。六座副本，六个死局，七个人只能活一个。 她必须赢……一枚铜钱
  • 0669阅读
    我当上帝那些事儿神作潜力完结
    作家马伯庸倾情推荐，想象与哲思的极致碰撞！ 如果你成为了上帝，你会干什么？ 是创造宇宙，还是毁灭世界？ 当天才青年神无月意外得到一本神秘的“创世之书”，踏入一片不受现实束缚的空间时，他拥有了造物主的至高权柄： 他修改物理常数，把星系当作试验场； 他播下生命的种子，观测异质文明一路演化…… 而后，他将目光投向地球。 这一次，他决定展开一场测试人性的“生存游戏”。 当他的消息公布到地球上每一个人的耳中时，所有人都为之震惊。杨建东
  • 0737阅读
    人是机器神作潜力完结
    拉·梅特里的《人是机器》，是一部震动18世纪欧洲思想界的经典著作。它的破天荒之处在于——第一次将人视作信息与结构的载体，也即书名所说的“人是机器”。 拉·梅特里在书中指出，人类的思想、情感与意志并非源自灵魂，而是身体结构与神经系统运作的结果。换言之，人不过是一部极其复杂的自然机器。这一大胆设想不仅挑战了传统宗教与哲学关于“灵魂”的观念，也为后来生理心理学、认知科学乃至人工智能思路打开了一条道路。 它的激进推论是：如果思想只是物质复杂组装的产物，那么理论上：只要把物质组织到足够精密，机器就可以产生思想与意识。 机器人普及的世界，是不是终将到来？[法]朱利安·奥弗雷·德·拉·梅特里
  • 08100阅读
    一生的读书计划神作潜力完结
    本书为18岁到80岁的读书人推荐的一份规模宏大的读书计划，这个读书计划内有举世公认的欧美思想家与文学家的100册杰作，内容包括始于荷马，迄于现代的戏剧、诗歌、小说、散文、历史、传记、自传等。 本书采取与读者作简短对话的形式，每次只用五百到一千字勾勒作品或作者的轮廓，诱引读者读他所介绍的每一本书。这些介绍生动活泼，有时强调作者的生涯与人品，有时摘要叙述作品内容，有时援用权威人士的意见，有时劝告读者别为一般错误见解所迷惑，有时对读者早已熟识的作家如莎士比亚、歌德做出新的评价。费迪曼强调编撰此书的意图是使读者的脚步迈向书店或图书馆，并提供开门的钥匙，让读者自己去挖掘一生无穷尽的宝藏，不断拓深知识领域，达到渊博多识。克利夫顿•费迪曼
  • 09185阅读
    画地为牢文学作品集：友情是想触碰又收回手神作潜力完结
    通讯录里总有几个不再联系的人。也许有过一次无法挽回的背叛，也许只是话越来越少，再见面时，对方身边已有了更亲密的朋友。这本书选的正是这样的关系：不圆满，不纯粹，也不善始善终。 友情是世间最复杂的羁绊，它不像亲情般血脉相连，也不似爱情般非君不可。在《画地为牢文学作品集》中，我们看到的不是高歌猛进的知己之交，而是那些在岁月长河中破碎、疏离、误解甚至背叛的“不完美”关系。 友情没有亲情的牵绊，也没有爱情非要一个结局，所以它最自由，也最脆弱。那些被我们假装洒脱放下的旧事，并不会因为断了联系就消散。古今中外的篇目放在一起读，百年前的人与今天的读者，尝到的其实是同一种酸涩。 这是一本不歌颂友情、只品鉴友情的书。读别人的分开，或许正是在读自己通讯录里那个再也没有拨出的名字。奥斯卡·王尔德 等
  • 1086阅读
    越洋情书：波伏娃笔下的爱与自由神作潜力完结
    女性主义代表人物波伏娃，用 304 封书信，书写长达 17 年的跨洋情爱。 1947 年，波伏娃赴美巡回演讲，在芝加哥遇见了美国作家纳尔逊·阿尔格伦。一个是巴黎左岸知识圈的核心，一个来自美国中西部粗粝的街头；一个惯于思辨，一个凭本能写作。差异没有成为障碍，反而成了吸引力的源头——此后的二十年间，他们用一封封越洋书信，在两个大陆、两种文明、两种生活之间，维系着一段罕见而诚实的感情。 这些信不只是情书。它们是《第二性》《名士风流》写作年代最真实的心路现场：波伏娃在信中谈论哲学、写作、政治与孤独，也谈论牵挂、等待与分离。她没有因为爱而收起锋芒，也没有因为思想而压抑情感。两个自由的灵魂在差异中相互照亮，也在差异中抵达了彼此无法再靠近的边界，最终平静地走向各自的命运。 思想让我们认识波伏娃，这些信让我们看见她。而她用二十年证明了一件事：爱与自由，从来不是一道选择题。[法]西蒙娜·德·波伏娃
  • 11168阅读
    道德经·九贤论道（历代注家白话汇解）神作潜力完结
    《道德经》五千言，字简而意远。两千年来注家不绝，却始终各执一说，本书选取九位身份、境遇迥异的古人，他们身处不同时代，对同一部经典作出了迥然不同的理解。 开篇一个"道"字，河上公读出养身，王弼读出本体，苏辙读出心性。同是治世，唐玄宗正当开元盛世，说的是清静无为而天下自治；宋徽宗自号道君皇帝，把清静寡欲写进御注、颁行天下；朱元璋起于布衣，话从饥荒与战乱里取出，句句落在吏治民生。 九个人相隔千年，从未谋面，却在同一页纸上彼此参照，也彼此辩难。真正的道不在任何一家之言里——它在你读完这场延续两千年的对话之后，自己心里慢慢升起的那一点思辨。[春秋]老子著 见山河编译
  • 1277阅读
    三年（契诃夫中篇小说）神作潜力完结
    商人拉普捷夫与尤丽雅缔结缺少爱情的婚姻，历经三年岁月流转，爱意错位变迁。借家庭纠葛，描摹旧俄社会里普通人的情感困境与生存真相。[俄]契诃夫
  • 1353阅读
    捉弄·未婚妻（契诃夫女性成长短篇小说两则）神作潜力完结
    《捉弄》讲述少年假意示爱、肆意戏弄少女，闹剧收场只剩难堪与怅惘；《未婚妻》讲述女子挣脱婚约束缚、奔赴远方，寻得独立新生与人生方向。[俄]契诃夫
  • 14822阅读
    一定要不停记录自己神作潜力完结
    记录不仅可以帮助我们梳理过往的经历、让内心的感受更清晰，还能提升我们规划和管理生活的能力。 这是一本以记录为核心的自我疗愈指南。全书分为两部分：第一部分聚焦记录的力量，作者结合自身经历，分享了记录如何帮助自己走出人生低谷、摆脱迷茫，实现自我成长与自我疗愈；第二部分强调“记录为舟，生活为岸”，作者分享了在不停记录自己的过程中获得的经验和感悟。此外，书中还提供了大量即学即用的记录模板，从情绪急救日记到自我对话清单，从社交断舍离清单到人生年度大事件…… 本书不要求读者复刻作者的记录方式，而是引导每个人在持续记录中到适合自己的方法，在记录和书写中完成自渡和自愈，最终活成真实、完整的自己。晴叙
  • 15187阅读
    美丽新世界神作潜力完结
    《美丽新世界》描绘了一个反乌托邦未来：人类经基因工程预设为不同种姓，在“幸福”中丧失个性与自由，成为社会驯服的零件。[英]阿道司·赫胥黎
  • 1641阅读
    在酒楼上（鲁迅短篇小说）神作潜力完结
    “我”返乡途中在酒楼偶遇旧友吕纬甫，昔日热血青年如今颓唐麻木，二人闲谈间尽显理想被现实消磨的悲凉与人生的寂寥。鲁迅
  • 1774阅读
    16小时断食术神作潜力完结
    1. 最新医院研究结论表明：吃什么和怎么吃都不重要，重要的是要增加“什么都不吃”的时间。不需要市面上那些花里胡哨的返年龄商品，现代人最需要遵循的健康法，就是每天保持16小时不吃东西。 2. 现代人的健康问题，大部分是因为“吃得太多”导致的。究其原因，其实是被我们当做常识的“一日三餐”的观念就是错误的。一天吃三顿，这就已经“吃多了”。在日本，“一日三餐”的概念其实是一百多年前才提出的，相比于人类几万年的历史，“一日三餐”仅仅是江户时代的木工、石匠、农民、武士这些以体力活动为主流的背景下提出的用餐习惯。对于现代社畜来说，哪里用得着干体力活，根本就是电脑桌前坐一天。“一日三餐”这种被大家当做常识的说法，其实没有科学根据。 3. 吃多了有什么坏处呢？变胖是当然的，更本质的问题是让消化系统和内脏的负担增加。从食物进入胃里开始，经过消化、分解、吸收营养，大约需要10个小时以上。一日三餐导致的结果是让脏器在24小时里根本没有休息的机会，还没消化完上一顿，就开始消化下一顿，让食物的影响根本没办法好好被吸收，最终使身体的免疫力下降，导致感冒、肺炎、过敏、衰老甚至癌症。 4. 为什么要空腹16小时呢？10小时消化完，再让肠胃休息6小时。这样一来，人体会进入一种轻微饥饿的状态。在这种状态下，肠胃会不依赖食物的能量，而是自己进入活性化状态，科学上的说法叫“自体吞噬（autophagy）”。所以，断食16小时，就能防止众多疾病，还能延缓衰老，可以说对身体非常有益。 5. 但是，一天16小时不吃东西，听起来还是很难做到啊。别担心，其实很简单。首先睡觉8小时本来就不吃东西，然后保证晚餐在晚上8点之前吃完，然后跳过早餐，第二天中午12点-12点半吃午饭就行。刚开始你可能会因为不吃早饭导致上午工作无法集中精神，可以吃一些干果、蔬菜色拉或者奶酪来过度，等到习惯之后，早上一杯咖啡就足够你撑到中午了。 6. 最后一点注意，就是每个人体质不同，如果断食16小时对个人有很大影响，也请停止。另外，如果你是习惯健身的人，也不要使用断食法。大量锻炼加上断食，反而会导致肌肉萎缩。青木厚
  • 1853阅读
    干校六记（轻经典）神作潜力完结
    本文选自杨绛著《杨绛散文》，是杨绛先生回忆特殊岁月的纪实佳作。文中以细腻笔触，讲述她与丈夫钱钟书等人在干校的下放生活，涵盖离别、劳动、日常等诸多片段。从下放的艰难，到劳作的艰辛，再到生活中的点滴温情，无不展现。在平淡的叙述中，饱含着对过去的深刻反思。杨绛
  • 19236阅读
    致流浪的母亲：我的童年发生在世界尽头神作潜力完结
    本文选自《花城》杂志 2026 年第 4期。 1988年的富蕴像一场梦，冰蓝的额尔齐斯河是它与现实的界限。 九岁的她矮小得猜不出年龄，被叫作小帕克。她第一次和母亲真正同住，才看清想象里完美的母亲，不过是个手艺差、性子急、靠铁皮火墙取暖的普通女人。 零下四十度的冬天，母女俩挤在杂货铺的货架后入睡。 童年的下半场，在这世界尽头重新开场。李娟
  • 2061阅读
    余生：《四个春天》之后的故事（轻纪实）神作潜力完结
    【曾经记录《四个春天》的摄像机，如今对准离散与病痛】 五个人的家，只剩下两人。父亲病逝，母亲卧床，姐姐早亡，哥哥肺癌晚期。 但歌声没断——母亲在父亲灵前唱《何日君再来》，哥哥化疗后仍作曲《回归的致意》。他们用一生回答：如何面对死亡，怎样好好告别。《人物》杂志 李斐然
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arXiv · q-bio.NC

1小时前更新
  • 01
    Qualiaphobic artificial neural networks (and why to build them)
    This paper introduces qualiaphobic AI: artificial neural network architectures that are hostile to theories of consciousness. I show that qualiaphobia can be well-justified by knowledge about theories of consciousness, like when such theories are trivial or unfalsifiable or contradicted by overwhelming scientific evidence. It can also be justified by how theories of consciousness must be grounded in phenomenology, as well as how current popular theories of consciousness are applied to AI. I idenErik Hoel
  • 02
    Spike-to-Field Mechanisms of Turbulence-Like Dynamics in Spatial Spiking Neural Networks
    Neural avalanches and turbulence-like brain dynamics are usually measured after neural activity has been coarse-grained into continuous fields, leaving open which spike-level mechanisms can generate these macroscopic observables. We build a spatial leaky integrate-and-fire spiking neural network and explicitly transform spikes into activity-density and Hilbert phase fields. A delayed, distance-dependent, passive-dendrite regime reproducibly generates turbulence-like field structure, including hiZequan Liu
  • 03
    K-prop: Deep Online Learning by Backpropagating Temporal Kernels
    Self-recurrence represents an important component for temporal processing in neural networks, both artificial and biological, where it appears naturally in the form of leaky integration. However, due to the complex temporal dependencies of the gradient, an efficient and effective method of online training is still lacking. Here we propose K-prop, a novel online learning method for leaky neural networks. It dramatically reduces the computational and memory cost of real time recurrent learning (RTBingkun Liu
  • 04
    TrajLift: Lifting Memory Recall Trajectories with Latency-Modulated Heat Diffusion
    Verbal memory retrieval carries rich diagnostic information for Alzheimer's disease through the order, hesitation, and categorical organization of recalled words, yet computational modeling of this retrieval process remains largely unexplored. A key challenge is that timing and hierarchical structure are diagnostically entangled: the diagnostic meaning of retrieval timing depends on its hierarchical context. We propose TrajLift, a spectral framework that models verbal recall as timed trajectorieJiawen Kang
  • 05
    Language processing in the autistic brain: A meta-analysis of neuroimaging studies across modalities and age
    Language is central to social communication, which is altered in autism, and language abilities vary widely among autistic individuals. How the autistic brain processes language is central to understanding autistic communication. Yet neuroimaging studies report inconsistent findings on how autistic brain activity is altered during language processing. We synthesized 45 fMRI and PET studies (753 autistic and 777 non-autistic participants) with seed-based d mapping with permutation of subject imagHanlin Wu
  • 06
    MICE: Multi-animal Interaction Context Encoder - A Hierarchical Foundation Model for Mouse Behavior
    Quantifying mouse behavior from pose is a foundational tool in neuroscience, ethology, drug discovery, and animal welfare. Self-supervised foundation models are a natural fit, but a foundation model for mouse behavior must handle social behavior - many behaviors that matter (aggression, courtship, mounting, allogrooming) are inherently multi-animal. Existing self-supervised pose models fall short: they encode each animal independently and discard interaction signal, hard-code the animal count, aYen-Shuo Su
  • 07
    From MNH to the Friedman--Komogortsev Method---which changes improve eye-movement classification?
    The Friedman-Komogortsev Method (FKM) is a rule-based classifier of fixations, saccades, and post-saccadic oscillations in 1000-Hz recordings, developed from the modified Nyström-Holmqvist algorithm (MNH) and used in several recent studies. FKM changes MNH in many ways at once: it centres MNH's Savitzky-Golay filter, adds a position-based test for whether an apparent post-saccadic oscillation continues the saccade, adds rejection tests, and changes several thresholds. We asked which of these chaLee Friedman
  • 08
    Learning Actionable Information Landscapes for Multimodal Active Sensing in Hawkmoths
    Animals integrate information across sensory modalities to guide exploration, suggesting that they maintain internal estimates of where actions are expected to reduce uncertainty. However, how such action-conditioned information maps are learned from multimodal sensory experience remains unclear, as previous studies have been largely confined to unimodal sensing frameworks. We introduce a multimodal predictive-coding framework for learning uncertainty-reduction maps from visual and mechanosensorAbdelrahman Sharafeldin
  • 09
    Perception, Not Reasoning, Limits Visual Theory of Mind
    Vision-language models pass text-based false-belief probes at near-human levels but drop by over twenty percentage points on abstract panels the moment the same problem is conveyed visually. The consensus diagnosis is conceptual, prescribing new belief-reasoning modules. We argue the dominant bottleneck is perceptual: not what the model cannot reason about, but what it cannot see. We propose a five-condition dissociation protocol that holds the reasoning task constant while varying perceptual fiMohamed Rayan Barhdadi
  • 10
    NeuroHorizon: Long-Horizon Forecasting of Neural Population Activity with Hierarchical Memory
    Long-horizon forecasting of neural population activity tests whether a model has captured dynamics that remain predictive well beyond the observed history. Prediction quality typically declines as the horizon grows, yet neither short-horizon accuracy nor teacher-forced evaluation, which supplies the true activity preceding each predicted step, reveals how well models sustain predictions from an initial history alone. We compare direct multi-step prediction and autoregressive rollout on spiking rPeng Jiang
  • 11
    Pixels over Symbols: Sensory Realism Improves Behavioral Alignment in Models of Cognition
    Computational models of cognition have traditionally relied on abstract symbolic inputs that approximate sensory experiences with simplified vector representations. This simplification reflects historical computational constraints and a long-held assumption that the details of sensory realism are incidental to the study of cognitive processes. Recent advances have enabled the development of sensory-realistic models capable of performing diverse cognitive tasks, yet whether sensory realism meaninHao Yuan Bai
  • 12
    Path-dependent triage: Early judgments lead conversational AI chatbots to miss mental-health emergencies
    People increasingly bring mental-health concerns to consumer AI chatbots. In these conversations, clinically relevant information rarely arrives all at once. Instead, it unfolds over multiple turns, often in response to the questions the chatbot asks. Recognizing risk therefore depends on how a chatbot integrates newly disclosed information (inference) and on the questions it asks on each turn to elicit this information (context-seeking). Here we evaluated the conversational triage performance oVeith Weilnhammer
  • 13
    A hair-thin implant opens the entire depth of the mouse brain to revisiting the same structures at subcellular resolution
    Ultrathin multimode-fibre endoscopes provide minimally invasive access to subcellular structures throughout the depth of the mouse brain. Here we introduce a chronically implantable interface with a diameter of 144 μm, about the thickness of a human hair, that extends this capability to longitudinal imaging, enabling repeated access to the same fine structures over extended periods. The system supports weeks-long tracking of individual dendritic spines, allowing quantitative comparison of theirMiroslav Stibůrek
  • 14
    Decoding spatial and semantic information from large-scale visual cortical activity for natural-movie reconstruction
    Reconstructing natural visual experience from cortical population activity is a central challenge in neural decoding, particularly for calcium imaging, where signals are noisy, temporally filtered, and paired neural-video data are limited. Here we present Ca2REAL (Calcium Activity to Reconstruct Events, Appearance, and Layout), a neural-to-video framework that conditions a pretrained video diffusion model through separate layout and semantic controls derived from calcium activity. Using measuredYukai Huang
  • 15
    Same Behavior, Different Mechanism: What Finite Experiments Can Certify About Integrated Information
    Interpretability, AI auditing and assessments of machine consciousness increasingly rest on mechanism-level quantities: functionals of a system's causal transition law that describe how it computes, not what it outputs. Experiments see that law only through finite, partial and noisy interventions. We ask when such a quantity is identifiable from an experiment's access, continuous in the mechanism and certifiable from finite data, and answer exactly for a deliberately demanding case - the integraLinqian Wu
  • 16
    Spiking neuromodulation: a linear control perspective
    Neuronal excitability is a nonlinear phenomenon, and the complexity of spiking experimental traces sometimes looks defeating. The present paper takes the view point that excitability is a neuromodulated property, and aims to demonstrate that the neuromodulation of spiking is amenable to the classical linear analysis tools of control theory. We illustrate the value of linear feedback analysis as an alternative to bifurcation analysis in the simple yet classical example of spiking modulation by thFulvio Forni
  • 17
    Do sEMG Foundation Models Improve Cross-Subject Generalisation?
    sEMG Foundation Models aim to learn general purpose representations over diverse subjects and recording conditions that boost performance on a variety of downstream tasks. However, existing evaluations make it difficult to discern whether pretraining alone is sufficient to combat the cross-subject overfitting which makes machine learning on sEMG so challenging. We conduct a systematic evaluation of three sEMG foundation models across three gesture classification datasets under both intra-sessionWilliam Raftery
  • 18
    Reversible Dynamics, Asymmetric Actions: Parking as a Trajectory-Level Affordance
    Drivers are often told to back into a tight parking space, not drive in nose first. The advice looks paradoxical, because a slow car is dynamically reversible: reverse its speed and replay the steering backward, and it retraces a feasible path. Played backward, though, reverse-in shows a car driving forward out of the space. Reverse-in and forward-in are different tasks: they share a start position but end facing opposite ways. We separate three clearances between car and obstacles. Static fit $Adam Y. Shavit
  • 19
    Invariance before structure: two modes of emergent compression in representation learning
    Learned representations show striking invariance across biological and artificial neural networks, with different substrates and variations driven by drift, heterogeneity and initialisation. To understand this invariance, we propose Emergent Adaptive Representation Learning (EARL), a framework that distinguishes two modes of emergence in learned representations: state-space compression, where a learned representation gains predictive power over its own future beyond what the network's units canHardik Rajpal
  • 20
    Self-Supervised Learning of Local Predictive Directions as a Neural Computation
    Natural sensory dynamics are globally nonlinear but often exhibit simple local geometry, with nearby trajectories evolving preferentially along a small number of predictive directions. We ask how neural circuits could discover this geometry directly from temporal experience. We introduce Local Predictive Directions (LPD), a self-supervised framework that learns local directions whose projections maximally predict near-future trajectory evolution. LPD applies past-future canonical correlation anaMarco Zenari
  • 21
    Bearing, heading and the perceptual geometry of collective motion
    Traditional models of collective motion commonly assume that animals turn to match their neighbours' directions of travel. In the harmonic theory, decisions follow from a neural representation of direction, and a neighbour enters only as a stimulus at a bearing, the direction in which it lies. Here we show that a neighbour's spatial extent allows its orientation to enter through projection geometry alone, and the theory generates a matrix of coupling coefficients indexed by the neighbour's beariMohammad Salahshour
  • 22
    Learning Time-Varying Connectomes for Stable Behavior Across Development
    Neural circuits must maintain functionality to drive effective behavior while their size, topology, geometry, and intrinsic dynamics change across development. To model developing visuomotor circuits and behavior, we investigated whether a single compact generative encoding could produce functional recurrent controllers across such changes. Building on the HyperNEAT algorithm, we represented this program as a compositional pattern-producing network that received developmental time as an input toChristof Fehrman
  • 23
    Cell-type-specific modularity in E/I networks shapes dynamical regimes and computational capabilities
    Structural modularity is a ubiquitous feature of brain networks that shapes neural dynamics and information processing. Yet excitatory and inhibitory populations can differ in their modular organization, and it remains unclear how this asymmetry affects network dynamics and computation. Here, using dynamical mean-field theory and simulations of networks performing complex temporal tasks, we show that independently tuning excitatory and inhibitory modularity controls the dynamical regimes of balaEmmanouil Giannakakis
  • 24
    PINR-ESI: Physics-Informed Self-Supervised Implicit Neural Representation Framework for EEG Extended-Source Imaging
    EEG extended-source imaging aims to localize active cortical regions and characterize their spatial extent, yet supervised inverse networks typically depend on synthetic EEG-source pairs and may be sensitive to synthetic-to-real mismatch. We propose a physics-informed self-supervised implicit neural representation (INR) framework for spatial source reconstruction without paired source labels or simulation-based supervised pretraining. The lead field matrix encodes the source-to-sensor volume-conZhiyong Zhou
  • 25
    Synchronized Hearts, Desynchronized Brains: A Nonlinear Dynamics Perspective for Function and Failure
    Both the heart and the brain are built from electrically excitable cells, yet the emergent dynamics of these organs could not differ more. In the myocardium, a coherent traveling wave of action potentials ensures coordinated contraction; in the cerebral cortex, distributed, irregular spiking underlies efficient information processing and the generation of behavior. Here, we illuminate the principles that underlie the emergence of such distinct nonlinear dynamics using concepts from complex systeIrene Pellini
  • 26
    Time-Division Multiplexing: The Operational Rhythm and Temporal Organization Layer of Digital Life
    Continual agents must handle urgent interaction while retaining alternatives, replaying errors, and committing safe long-term changes. A previous digital-life framework distinguishes online (busy) and offline (idle) channels, but leaves open whether these are separate programs or phases of a common process and how their operations should be ordered. Motivated by recent observations of rapidly alternating perceptual representations in primate cortex, we develop a temporal organization layer withHaibin Tong
  • 27
    Mind Control of LLMs via Closed-Loop Stimulation: Out-of-Distribution Robustness
    Brains and large language models need not be considered equivalent systems to reveal an interpretable commonality: both exhibit high-dimensional, nonlinear dynamics whose behavior can only be modeled imperfectly. This creates a shared challenge whenever we seek to intervene in their dynamics. A controller may either rely on a model identified around a particular operating regime and risk failure as the system moves away from that regime, or explicitly account for uncertainty and a changing interKasra Fallah
  • 28
    A minimal E/I circuit model explains differential recovery from amblyopia under TTX and reverse occlusion
    Recovery from amblyopia beyond the critical period remains a major challenge in visual neuroscience. Experimental studies show that transient inactivation of the fellow eye with tetrodotoxin (TTX) produces stronger and more persistent recovery than reverse occlusion (RO), despite both interventions reducing competition from the fellow eye. The circuit mechanisms underlying this difference remain unclear. We develop a minimal cortical circuit model combining excitatory-inhibitory population dynamLawrence Udeigwe
  • 29
    A Bayesian Optimized Biquad Filter-Burg Model for Real-Time EEG Phase Estimation
    Real-time phase estimation on stimulus-aligned transient EEG is critical for closed-loop neuromodulation systems targeting the theta-band, yet most real-time phase estimation methods have been developed and validated on resting-state, high-fidelity signals in the alpha band. Recent work has pursued deep learning architectures, while individualized classical bandpass filter tuning remains underexplored. This study characterizes the spectral and temporal properties of non-anticipative bandpass filIvan Martinez-Kay
  • 30
    Curriculum unlearning in humans and neural networks
    During learning, humans often benefit from curricula that teach simple rules before exceptions. However, we lack a computational explanation for this phenomenon. Here, using a canonical behavioural task and modelling with neural networks, we develop and test a theory for why simple-to-complex curricula succeed. We show that during learning, both humans and neural networks show simplicity biases, a tendency to learn simple rules that are underfit to the data. In neural networks this bias is accomJirko Rubruck
  • 31
    Memory flows: geometry and dynamics of sequential retrieval in input-driven Hopfield networks
    Associative memory models classically describe retrieval as convergence to stored patterns, but the theory of sequential retrieval remains comparatively limited. We develop a two-timescale input-driven Hopfield network in which fast associative retrieval is modulated by a slow feedback variable evolving over a prescribed memory-transition graph. This yields autonomous, graph-constrained transitions while preserving analytical tractability. Using slow-fast and geometric singular perturbation theoSimone Betteti
  • 32
    When Model Complexity Matters in Cross-Subject Naturalistic fMRI Prediction
    Increasingly complex neural models predict blood-oxygen-level-dependent (BOLD) responses to naturalistic stimuli, but the predictive value of this added complexity remains unclear. We ask when pretrained stimulus representations help and how much downstream complexity is needed, with and without recent measured BOLD history. We compare linear diagnostic references and nonlinear predictors across HCP movie fMRI (154 subjects), BOLD Moments (10 subjects), and Algonauts 2025 (4 subjects). Under a sJunhao Zhao
  • 33
    Fly Whiskers Meet LiDAR: Robust Navigation under Sensor Failure
    We extend FLYNN, a leaky integrator recurrent network wired on the Drosophila melanogaster connectome, with a 32-ray 2D LiDAR interface that requires no learned fusion layer beyond a scalar input gain. A 270 degree frontal scan at 8 m range is injected as inverted proximity into the 37 BM Vib head-bristle neurons. Across 24 paired comparisons in a four- state vision matrix with LiDAR on or off, FLYNN-LiDAR has 17 significant wins, 5 nonsignificant comparisons, and 2 significant losses against thAli Mahzarnia
  • 34
    Evolved Spiking Neural Networks for EEG Seizure Detection: Calcium Dynamics and Delay Mechanics
    Neuroevolution can discover compact network designs that are hard to specify by hand. The EONS framework evolves the topology, weights, thresholds and delays of neuromorphic spiking networks without gradients. We tested whether giving integrate-and-fire (IF) neurons an activity-dependent calcium current (Ca-IF neurons) improves evolved networks for EEG seizure detection, with calcium parameters fixed, shared across a network, or evolved for each neuron. On 10 held-out CHB-MIT patients never seenTuba Aksoy
  • 35
    Intrinsic network dynamics catalyze switching in functional connectivity states of the brain
    Dynamic functional connectivity (dFC) reflects ongoing reconfiguration of large-scale brain networks, but the temporal organization and network processes underlying spontaneous state transitions remain poorly understood. We developed functional connectivity state switching (FCSS), a phase-coherence-based framework that tracks multiscale changes in dominant whole-brain connectivity configurations. In Human Connectome Project fMRI, FCSS was strongly evoked by cognitive state and condition switchesSteven S. Kang
  • 36
    AVID: A 5T fMRI Dataset for Benchmarking Auditory-induced Visual Mental Imagery Decoding
    Visual mental imagery (VMI) decoding uses brain activity to reconstruct internally generated visual scenes, providing a potential pathway for externalizing internal experiences and developing neuroprosthetic communication interfaces. However, progress is limited by the lack of dedicated, training-scale VMI datasets. Current VMI paradigms often rely on visual prompts or short-term memory images, introducing visual and mnemonic confounds that make it difficult to disentangle neural activity associShiqi Shen
  • 37
    Prior Action Control Causally Alters Language-Model Plasticity
    Two copies of one language model start from identical weights and receive the same rewards during training. For one copy the rewards depend on its own answers. The other copy is yoked: it receives the first copy's rewards no matter what it answers, a design taken from the learned-helplessness experiments of animal learning. We ask whether the copy whose rewards depended on its answers, the copy with control, later learns a new task faster, that is, whether control changes the model's plasticity.Marc-Andre Schulz
  • 38
    Modeling Visual Cortex with Layerwise Multiscale Manifold Capacity Maximization
    Task-optimized deep neural networks have risen to prominence as the most predictive phenomenological models of responses in primate visual cortex, but leave much to be desired from the perspective of biological plausibility. One such limitation is the reliance on precise credit assignment through global backpropagation of error signals. Recent work has shown that this weakness can be circumvented by requiring each subsequent stage to solve a distinct and increasingly complex task, allowing for lThomas Yerxa
  • 39
    Statistical mechanics of spontaneous behavior
    Why do a few behaviors fill most of an animal's time? The usual answer is that these behaviors are started more often, because learning and reinforcement favor them. Here we show that how long a behavior lasts can, by itself, explain much of what is observed. We consider a system that runs until it meets a constraint, such as a wall, and then resets. The fraction of time it spends in each behavior then follows the Boltzmann law, and the partition function is the mean time between resets. The fouDaniel Y. Takahashi
  • 40
    Do agents need to sleep?
    LLM-based agents, which increasingly operate persistently across sessions and accumulate memory through interaction, already exhibit the familiar symptoms of unchecked plasticity: semantic drift, degraded retrieval precision, propagation of stored errors, and saturation of memory capacity. Drawing on the selectionist "ringing, resonance and renormalization" (RRR) account of sleep, we propose that each of its three phases maps onto an operation feasible in digital memory architectures. EngineersIdo Haber
  • 41
    The (Butter)fly Dream: Linear Separability of World-Model Rollouts in a Connectome-Constrained Visual Model
    Zhuangzi dreamt he was a butterfly and, on waking, could not tell which was the dream. We ask a version of his question of a model of the fly brain: placed inside a world generated by a world model, can a fixed brain tell that the world is a dream? We treat it as a question about what a connectome-constrained model trained on one task makes available beyond that task: do its responses make the defects of a dream linearly decodable? The observer is a published model of the fly visual system trainJunichiro Niimi
  • 42
    A Planar Switching Neuron Shares Logarithmic First-Spike Latency with Its Three-Dimensional Parent But Not Its Onset Mechanism
    Can a reduced neuron model reproduce first-spike latency scaling while changing how a stimulus initiates sustained firing? We compare a piecewise-linear planar Neurosimilator with its three-dimensional parent. Both exhibit logarithmic latency dependence over the investigated input intervals, with different fitted coefficients. The mechanisms differ. In the parent, sustained spiking and a stable resting focus coexist in a spiking--rest bistability regime. An abrupt step accesses spiking, while slGiorgio Sonnino
  • 43
    S1CogBench: What System One Decision Models Can and Cannot Do on Cognitive Experiments
    Language models are no longer used only to generate text. Software also asks them for decisions, in routing, guardrails, and automated gates. System One decision models, also called typed decision models, such as Jev and Laya, return one fast decision over the legal options, leaving no text to inspect. However, a fast, well-formed decision does not show that the model used the evidence. Cognitive experiments can test this, because they vary task demands and measure how behavior changes, yet exisDengzhe Hou
  • 44
    Adversarial robustness does not entail human-aligned categorization
    Adversarial training can improve some forms of correspondence between artificial and biological vision, but whether robust classifiers acquire human-aligned classification behavior remains unclear. We generated 1,008 controversial stimuli by optimizing latent inputs to a pretrained GAN to elicit high-confidence disagreements between pairs of robust ImageNet classifiers. We compared four adversarially robust ImageNet classifiers - ResNet-101, ViT-B, ConvNeXt-L, and Swin-L - with two-alternative cItay Reznik
  • 45
    From Connection Loss to Collision: Closed-Loop Fault Assessment of a Fly-Connectome SNN
    The public release of the complete adult fruit-fly brain connectome enables brain-scale spiking-network studies, motivating closed-loop assessment of connection loss. We test a connectome-derived controller in synthetic pursuit-escape and check record consistency. Across 576 test episodes in paired campaigns, the baseline mapping at 50% connection-row deletion yields 11/48 proportional and 0/48 relay collisions by 1 s, despite paired P/R trigger/burst schedules. The prespecified secondary relay-Shuchao Gao
  • 46
    Geometric and algebraic inference in humans and neural networks
    Humans possess a remarkable ability to draw inferences from limited data. While some inferences are made intuitively from past experience, others require online reasoning based on novel information given in context. Here, we formalize these strategies, which we term geometric and algebraic inference, and study their computational tradeoffs in humans and neural networks. The geometric strategy gradually shapes representational geometry to reflect underlying relational structure, making subsequentJacob Russin
  • 47
    Hyperbolic embedding of higher-order simplicial networks
    Many biological interactions involve groups rather than pairs, as when several proteins assemble into a multi-protein complex. Simplicial complexes naturally capture these collective interactions. Existing hyperbolic embeddings represent network hierarchy and similarity through a few interpretable coordinates, but rely only on pairwise links: they cannot distinguish three units engaged in a common interaction from three units connected only in pairs. We introduce here the hyperbolic higher-orderMartin Guillemaud
  • 48
    Expression of White and Gray Matter Autism Functional Network Connectivity Signatures in Infancy
    Functional connectivity studies have provided valuable insights into altered brain organization in autism spectrum disorder (ASD). However, most functional connectivity studies focus exclusively on either gray matter (GM) regions or white matter (WM) tracts and examine specific age groups, rather than investigating their functional interactions across brain development. This limits our understanding of how GM-WM functional interactions evolve developmentally and may obscure important aspects ofQiang Li
  • 49
    A Low-Rank Space Captures Linear Alignment Between LLM and Human Neural Activity During Naturalistic Language Listening
    Large language models (LLMs) are increasingly used as computational models of human language processing, yet it remains unclear which components of their representations drive alignment with neural activity. Here, we use ridge reduced-rank regression to identify the brain-predictive subspace of LLM representations: the representational directions that support linear prediction of neural responses. Across three naturalistic language-listening datasets spanning intracranial electrophysiology and fZach Paris
  • 50
    Latent Prediction Yields Cross-Subject Alignable Representations in Sensory-Evoked fMRI
    Decoding sensory-evoked functional magnetic resonance imaging (fMRI) data is a central analytical tool in cognitive neuroscience. Here we ask whether self-supervised learning (SSL), which has been scarcely explored in this domain, can yield representations that support strong downstream performance. To do so, we adapt a joint embedding predictive architecture (JEPA) to train participant-specific encoders on brain data alone. The encoders never see the stimulus images or any representation deriveSerwan Jassim
  • 51
    Recognition of auditory objects from continuous and ultra-sparse spike streams in neuromorphic devices
    Energy consumption is a major concern for modern artificial intelligence (AI) applications. The brain is thought to achieve energy-efficient computation through sparse coding schemes. By emulating the spiking dynamics of the brain, neuromorphic chips hold the potential to realize energy-efficient AI. In this work, we use birdsong to demonstrate that auditory object recognition can be achieved using ultra-sparse coding. Feature-detecting neurons tuned to short temporal features ($\sim$37 ms), samLeonardo E. S. Tavares
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