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【数智周报】张一鸣以6700亿元登顶中国首富，刷新中国首富财富纪录；阿里巴巴与Apple达成合作，将千问集成至Apple智能；Anthropic提交IPO注册文件，拟以“ANT”为代码在纳斯达克上市
（10 月 26 日-31 日）OpenAI据称将新一轮融资目标下调100亿美元，拟以1.25万亿美元估值融资200亿美元；谷歌推出最新世界模型Genie 4，模拟时长翻倍至2分钟、首次实现音视频同步生成；Meta拟融资350亿美元并计划推出600亿美元股票发行计划；中信证券：GPT-6 Astra进入机器人控制，物理…
来源：钛媒体 · 本地全文 站内详情人形机器人的第一份公账，Agility Robotics 上市前夜的深度解析
Agility Robotics 将于 11 月 5 日以「AGLT」登陆纳斯达克。全球首家在美股挂牌、且拥有真实商用人形部署的"纯血"公司。
来源：钛媒体 · 本地全文 站内详情小学生都可以看懂的例子，揭示为什么产销协同消除不了KPI矛盾，反而会引爆它？
各部门KPI全满分，公司ROIC却跌到3%？砸了千亿搞数字化转型，S&OP产销协同为何越开越乱？用极简的“两笔需求三颗料”，当场拆穿管理学的幻觉：KPI根本不是部门冲突，而是物理死锁！
来源：钛媒体 · 本地全文 站内详情Edge AI Daily 早报（11月1日）
AI叙事进入资本配置的周期性重估：纳斯达克录得2025年3月以来最差单月，Meta、Alphabet、Amazon财报利好却遭抛售，四巨头AI资本开支把自由现金流砸回负值，高盛预计2026年合计达7250亿美元；标普将Meta信用展望下调至负面，为其首次因AI基建支出获负面展望。一级市场同步降温，OpenAI融资目标从…
来源：钛媒体 · 本地全文 站内详情Apple CEO says the company doesn’t ‘want to ship AI for AI’s sake’
Apple's new CEO defended the company's current position in the AI landscape.
来源：TechCrunch AI · 本地全文 站内详情4 days left: How TechCrunch Founder Summit helps you make more useful connections to scale
On November 4 at Boston’s SoWa Power Station, get ready for a full day packed with meaningful networking opportunities, actionable insights, and connections tha…
来源：TechCrunch AI · 本地全文 站内详情Judge allows NAACP lawsuit over xAI data center pollution to move forward
An NAACP lawsuit accuses the SpaceX-owned AI company of violating the Clean Air Act.
来源：TechCrunch AI · 本地全文 站内详情Jync v1.9.0 · Webhook 告警与 ETL 批次
新增 Webhook 告警通知与 ETL 批次，ETL 连接类型扩到 7 种新库；同步链路修复了租约与连接池的一组问题。 新增 Webhook 告警通知：同步失败、CDC 异常等按分类推送，支持冷却时间与通用/钉钉/企业微信/飞书格式；地址加密存储，页面只回显尾号。 ETL 批次：同源同目标的多张表共享一对连接与一条调…
来源：OSC 开源中国 站内详情OpenAI reportedly lowers funding target for new round
OpenAI’s latest funding round doesn't seem to be living up to expectations.
来源：TechCrunch AI · 本地全文 站内详情DeepSeek 重磅发布全新 Agent 架构：AI 开始指挥 AI 干活
AI Agent 的下一个瓶颈，可能是人类自己#欢迎关注爱范儿官方微信公众号：爱范儿（微信号：ifanr），更多精彩内容第一时间为您奉上。
来源：爱范儿 · 本地全文 站内详情让AI拼我用了12天完成的1000片“纯白地狱”，它五小时就崩溃了
我耗时 12 天拼完 1000 片纯白地狱拼图，尝试交给大模型挑战，它 5 小时便陷入崩溃。不是 AI 不能拼，而是擅长看图描述的生成式大模型缺少精密测量与全局约束能力；传统机器视觉方案反倒可行。这件实验，也照见我们当下思考外包、本末倒置的认知困境。
来源：钛媒体 · 本地全文 站内详情首届北大光华讲席教授聘任仪式举行，有四位教授获聘，看看都是谁？
周黎安、陆正飞、刘玉珍、姜铠丰四位教授分别获聘为学院金光讲席教授、香港校友会讲席教授、台新讲席教授和拉卡拉讲席教授。
来源：钛媒体 · 本地全文 站内详情从“懂回答”到“能执行”：Zoho如何让AI走进企业业务
10月20日，在以“助力中国企业全球化成长”为主题的Zoho北京媒体沟通会上， Zoho不仅向外界展示了其最新的企业级AI全景战略，更试图回答一个当前行业的普遍痛点：当AI大模型喧嚣了两年之后，为什么大多数企业在业务中依然觉得AI“用不起来”？ Zoho全球副总裁Mathivanan一针见血地点出了症结所在：“太短的决…
来源：雷锋网 · 本地全文 站内详情酷瓜云课堂（网校企业版）v2.0.3 发布，PHP在线网校系统
更新内容 【增加】后台登录双因素验证（2FA/TOTP），支持在安全设置中开启 【增加】资金、积分、发票流水记录事前/事后余额 【增加】编辑器远程图片本地化开关（biz.editor.save_remote_image） 【优化】文件上传流程 【优化】补充数据类型声明，便于IDE跳转识别 【优化】去除不必要的强制类型转…
来源：OSC 开源中国 站内详情“开源才是护城河”：制造老炮把品胜的AI交给了00后
对赵国成而言，AI最终要落到生产力上；而考验丛泽龙团队的，将是怎么把一次次具体的创新变成可以复用、持续更新的能力。
来源：钛媒体 · 本地全文 站内详情🔥 优化及缺陷修复：开源 AI 无代码平台 NocoBase
汇总一周产品更新日志，最新发布可前往我们的博客查看。 NocoBase 目前更新包括三个分支： main、next 和 develop。** main： 截至目前最稳定的版本，推荐安装此版本。 next： 包含即将发布的新功能，经过初步测试的版本，可能存在部分已知或未知问题。主要面向测试用户，用于收集反馈和进一步优化功…
来源：OSC 开源中国 站内详情LRMoE: Demand-Side Load Re-Calibration for Efficient MoE Training on Memory-Constrained Nodes
Sparse Mixture-of-Experts (MoE) models offer scalable capacity for Web applications, but uneven routing creates computation and communication bottlenecks. Exist…
来源：arXiv cs.AI · 本地全文 站内详情Amortized Localized Posterior Inference for Model Calibration with Application to an Ocean Turbulence Closure
Model discrepancy may prevent a single calibration parameter from reproducing a physical response across the context domain. In addition, uncertainties in obser…
来源：arXiv cs.AI · 本地全文 站内详情ThinkJev: One Thought, Every Budget for Calibrated Typed Decisions
Many uses of language models end in a typed decision: a choice among a closed set of options, whose probabilities code can act on. Reading those probabilities f…
来源：arXiv cs.AI · 本地全文 站内详情OpenFrontiers: A Collection of Open Research Problems and a Benchmark for Scientific Rediscovery
Large language models (LLMs) have shown increasing promise in research-level problem solving, yet a comprehensive collection of such problems is still missing, …
来源：arXiv cs.AI · 本地全文 站内详情WebAnything: From the Wild Web to Scalable Agent Environments
Web agents require diverse, executable, and resettable website environments for reproducible training and evaluation. Human-assisted mirrors demand per-site eng…
来源：arXiv cs.AI · 本地全文 站内详情What Does an Ontology Catch? Curated, LLM-Generated and Data-Derived Ontologies as Checkers of LLM Agents over Knowledge Graphs
LLM agents that answer questions over Web knowledge graphs are increasingly wrapped in checks derived from the graph's ontology, on the assumption that a formal…
来源：arXiv cs.AI · 本地全文 站内详情Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis
AI agents can now write software from a plain-English description, but code that runs is not the same as code that does what was asked. This gap matters most fo…
来源：arXiv cs.AI · 本地全文 站内详情Detecting Covert Collusion between AI Agents through Partner-Outsider Positive Listening
AI agents that share a secret convention can coordinate through messages that look innocent, so a monitor that reads only the messages can miss them. We propose…
来源：arXiv cs.AI · 本地全文 站内详情Evaluating and improving AI agents for sequencing protocol understanding
Existing scientific-agent benchmarks rarely evaluate whether agents can reconstruct the exact molecular structures and generation workflows specified by sequenc…
来源：arXiv cs.AI · 本地全文 站内详情Seq@K: Evaluating Language Models Under Sequential Feedback
Language-model agents differ fundamentally from prior intelligent systems in their ability to learn from natural language in context. This capability enables ag…
来源：arXiv cs.AI · 本地全文 站内详情What Constitutes Food Similarity? Visual Representations and Retrieval in Indian Cuisine
Food similarity underlies retrieval, recommendation, substitution, and other food computing tasks, yet food representations are typically evaluated by identity …
来源：arXiv cs.AI · 本地全文 站内详情Verification Learning Theory: A Process Model of Checking and Retention in AI-Assisted Judgment
Accurate AI assistance can improve immediate judgments while reducing opportunities to practise the operations needed for independent performance. Verification …
来源：arXiv cs.AI · 本地全文 站内详情The Anatomy of Socio-Demographics in Pluralistic Offensiveness Modeling: When and Where It Helps, and the Role of Reasoning
Subjective judgments such as offensiveness often vary substantially across individuals, motivating pluralistic modeling approaches that incorporate annotators' …
来源：arXiv cs.AI · 本地全文 站内详情FilingLoop: Evaluating and Evolving LLM Agents for Corporate Disclosure Review and Revision
Public disclosure repositories such as SEC EDGAR support informed investment through web access to corporate filings. Supporting their review with language mode…
来源：arXiv cs.AI · 本地全文 站内详情Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
Spiking reservoir computing combines the training efficiency of fixed recurrent reservoirs with the energy efficiency of event-driven inference, where computati…
来源：arXiv cs.AI · 本地全文 站内详情SciGame: Let Agents Play the Scientific Discovery Games in the Real and Counterfactual World
Large language model agents are increasingly used for scientific discovery. However, existing benchmarks mix law inference with programming, score data fitting …
来源：arXiv cs.AI · 本地全文 站内详情VerifiedLab: Harnessing Knowns for Unknowns
Across human history, knowledge has undergone several transitions, from orality to writing and then to digital archives. At each transition, humans established …
来源：arXiv cs.AI · 本地全文 站内详情GARDEN: Generalist Autonomous Reward Design Through Evidence Navigation for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) enables teams of agents, such as robots and autonomous vehicles, to learn coordinated behavior, but what s…
来源：arXiv cs.AI · 本地全文 站内详情Understanding Large Language Models as Numerical Optimizers
Large language models (LLMs) have emerged as potential tools for numerical optimization. Despite promising results, their intrinsic optimization capabilities an…
来源：arXiv cs.AI · 本地全文 站内详情SkillMem: Compact External Skill Memory for Latent Multi-Agent Reasoning
Latent multi-agent systems reduce inference cost by keeping intermediate reasoning and inter-agent communication in continuous representations.\ Reusable skills…
来源：arXiv cs.AI · 本地全文 站内详情GAUSS: A Workload-Aware Analytical and Monte-Carlo Simulator for LLM Inference Serving
Large language model (LLM) inference has become an operational workload that fleets must provision, monitor, and bill against latency service-level objectives (…
来源：arXiv cs.AI · 本地全文 站内详情Algorithmic Bias from the Perspectives of Healthcare Professionals
This paper focuses on algorithmic bias of machine learning and artificial intelligence applications in healthcare information systems. Based on the quantitative…
来源：arXiv cs.AI · 本地全文 站内详情Assessing Language Models for Scientific Applications: Inertial Confinement Fusion as a Use Case
Advancing language models for specialized scientific applications requires evaluations of scientific fluency, physical reasoning, and quantitative analyses. Usi…
来源：arXiv cs.AI · 本地全文 站内详情PromptSense: Sentiment-Aware Mental Health Chatbot with Dynamic Prompting
Current Large Language Models (LLMs)-based mental health chatbots often lack sufficient empathy, contextual awareness, and safety mechanisms, potentially leadin…
来源：arXiv cs.AI · 本地全文 站内详情Evaluating Causal Reasoning in LLMs: A Case Study in the Challenges of Procedural Generation
Large language models (LLMs) appear to represent and reason about a large range of phenomena. In particular, recent studies have examined whether LLMs can accur…
来源：arXiv cs.AI · 本地全文 站内详情AI-Driven Digital Twin Framework for Warehouse Logistics Automation Optimization
In recent years, warehouse logistics optimization has increasingly focused on intelligent, data-driven systems to enhance operational efficiency. Conventional s…
来源：arXiv cs.AI · 本地全文 站内详情Too Hard, Too Easy, Just Right: Performance-Driven Challenge Adaptation in Virtual Reality Firefighter Training
Effective firefighter training requires practice under dynamic and stressful emergency conditions, yet real-world live-fire exercises are costly, risky, and dif…
来源：arXiv cs.AI · 本地全文 站内详情Post-Training Large Language Models with LLMON
Large Language Models (LLMs) treat all context tokens uniformly, lacking explicit separation between executable instructions and passive data. This leads to pro…
来源：arXiv cs.AI · 本地全文 站内详情Decompose, Don't Expand: Capability-Independent AI Systems by Construction
A recurring design choice in building AI systems is whether, when a task is too hard for a model, to expand the model (make it larger, better-prompted, fine-tun…
来源：arXiv cs.AI · 本地全文 站内详情SkillCT: A Multidimensional Benchmark and Execution-Free Baseline for Agent Skill Assessment
Agent skills package instructions, scripts, and resources for specialized tasks and are increasingly distributed through public Web repositories. However, exist…
来源：arXiv cs.AI · 本地全文 站内详情BridgeRouter: Gain-Aware Instance Routing over Cross-Modal Bridge Portfolios
Lightweight representation bridges make pretrained, task-adapted EEG foundation models executable on other biosignal modalities without retraining their backbon…
来源：arXiv cs.AI · 本地全文 站内详情DecompGym: Benchmarking LLM Agents on Designing Decomposition Algorithms
Benders decomposition and column generation solve large optimization problems by passing cuts, columns, and dual values between a master problem and subproblems…
来源：arXiv cs.AI · 本地全文 站内详情Prototype-Guided Dynamic Domain Modulation and a Large-Scale Multi-SKU Benchmark for Shampoo Bottle Surface Defect Detection
Industrial shampoo-bottle surface defect detection must operate across many stock keeping units (SKUs), where differences in bottle geometry, material, label la…
来源：arXiv cs.AI · 本地全文 站内详情From Natural Language to Real Schematics: An Automated Workflow for Power Electronics Schematic Synthesis
Designing power electronics converters traditionally requires intensive human expertise across topology sizing, commercial component selection, circuit simulati…
来源：arXiv cs.AI · 本地全文 站内详情GAAC: Lossless KV Compression for Bandwidth-Efficient LLM Inference on Personal Devices
Weight-only, lossy quantization substantially reduces the storage and memory requirements for serving large language models (LLMs), but the growing key-value (K…
来源：arXiv cs.AI · 本地全文 站内详情Disparity Laundering: Consensus Without Fairness in Clinical Multi-Agent Systems
Clinical large language models are increasingly fielded as multi-agent teams, on the assumption that deliberation averages out individual error. It does not ave…
来源：arXiv cs.AI · 本地全文 站内详情Rubricon: Automated Rubric Generation and Refinement for LLM Evaluation and Training
Rubrics enable reward assignment on tasks without verifiable answers, but are expensive to manually produce from scratch. We present Rubricon, a pipeline that g…
来源：arXiv cs.AI · 本地全文 站内详情FACTS-MAS: A Multi-Agent Architecture for Adaptive Forecasting from Heterogeneous Evidence
Real-world forecasting often requires integrating heterogeneous evidence whose predictive value varies across horizons, operating regimes, and domains. We intro…
来源：arXiv cs.AI · 本地全文 站内详情Verification-Guided Retrosynthesis: Reaction Feedback and Evidence Timing
Retrosynthesis planning seeks synthesis routes from purchasable starting materials to a target molecule. Search over predicted reactions can connect a target to…
来源：arXiv cs.AI · 本地全文 站内详情Inner-Learning: From Hand-Coded Beliefs to Declarative Knowledge in Trick-Taking Games
We present a declarative approach to belief-state modeling in trick-taking card games. Starting from a state-of-the-art Skat player, we automatically extract it…
来源：arXiv cs.AI · 本地全文 站内详情Game-Theoretic Foundations for Undiscounted Bisimulation Metrics
Bisimulation metrics offer a principled notion of task-relevant state similarity in reinforcement learning, but existing constructions and methods are largely c…
来源：arXiv cs.AI · 本地全文 站内详情CHORD: Cross-Model Hallucination Detection via Relational Graph Discrimination
Hallucination detection is critical for deploying large language models (LLMs) in real-world applications. Due to strong empirical performance, internal represe…
来源：arXiv cs.AI · 本地全文 站内详情Can LLMs Faithfully Solve Ontology Engineering Tasks? A Mechanistic Interpretability Study
Ontological knowledge underpins large language model (LLM) performance on knowledge-intensive tasks. However, existing evaluations of LLMs' ontological understa…
来源：arXiv cs.AI · 本地全文 站内详情Investor's Last Exam: Can AI Agents Do Equity Investment Without Seeing the Future?
Financial agents must form forecasts and investment judgments from decision-time evidence, with predictions evaluated against subsequent outcomes. Existing benc…
来源：arXiv cs.AI · 本地全文 站内详情Encode Once, Answer Many: Internalizing Context via Parametric Flow
Large language models are typically adapted to a task either by placing knowledge in the input context, which keeps it external and re-encodes it on every call,…
来源：arXiv cs.AI · 本地全文 站内详情Compute Has Shape: Self-Morphing the Internal Computation of Frozen LLMs
Test-time scaling improves large language models through additional computation, but how to adapt the topology of internal computation to individual inputs rema…
来源：arXiv cs.AI · 本地全文 站内详情SCOPE: Selective Critical-Step On-Policy Self-Distillation for Agentic Reinforcement Learning
Outcome-based reinforcement learning provides coarse supervision for long-horizon LLM agents: failed trajectories may contain correct steps, while successful tr…
来源：arXiv cs.AI · 本地全文 站内详情Masked Erosion: How Acceptance Gates Lose Redundant Safeguards in Self-Improving Agents
Self-improving LLM agents edit their own harness, the prompts and rules around a fixed model, and keep an edit only if an acceptance gate scores it higher on a …
来源：arXiv cs.AI · 本地全文 站内详情Agent Transfer Protocol: Server-Mediated Agent-to-Agent Communication Architecture for the Agentic Web
The Agentic Web needs to support continuous collaboration among agents from different organizations. These collaborative relationships may span multiple tasks, …
来源：arXiv cs.AI · 本地全文 站内详情Governance-Aware Federated Learning for Multi-Agent AI Systems: A Policy-Driven Framework for Trustworthy Collaborative AI
Federated Learning (FL) enables collaborative model training without exchanging raw data, but conventional FL provides limited runtime governance, evidence veri…
来源：arXiv cs.AI · 本地全文 站内详情Predict the Reward, Not the World: World Reward Models for ML Agents
Search-based machine-learning (ML) agents improve a solution by writing candidate programs, executing them, and keeping the best. Execution gives the search rel…
来源：arXiv cs.AI · 本地全文 站内详情DES-JEPA: Learning a Shared Vocabulary for High-Dimensional Discrete Event Sequences
Temporal foundation models such as Chronos and TimesFM generalize across domains through a shared numerical observation space. In contrast, discrete event seque…
来源：arXiv cs.AI · 本地全文 站内详情Accelerating Nonlinear MPC by Behavior Cloning with Separated Timescales: Application to Nuclear Reactor Load-Following
Behavior Cloning (BC) of expert controllers for multiscale dynamical systems is challenging: state variables evolving at widely separated timescales induce high…
来源：arXiv cs.AI · 本地全文 站内详情Value Probes: Learned Value Functions for Beam-Search Red Teaming
Automated red-team auditing of language models is an important way to evaluate safety-relevant behaviors. These audits implicitly search a tree of possible conv…
来源：arXiv cs.AI · 本地全文 站内详情From Leniency to Suspicion: How an Open Post-Training Recipe Changes Whom LLM Fact-Checkers Believe
LLMs increasingly fact-check online content with the poster's identity in view. However, it remains unclear which post-training changes how much a model's truth…
来源：arXiv cs.AI · 本地全文 站内详情An Alignment Benchmark for Enterprise Agents on Era by Eon
AI agents are widely used in enterprises to access business systems and act on them in pursuit of a goal. However, fulfilling a user's request can cause harm. E…
来源：arXiv cs.AI · 本地全文 站内详情PT$^3$: Prototype-Guided Self-Supervised Pretraining for Generalizable mmWave Human Point Cloud Representation
Multi-source millimeter-wave (mmWave) observations offer an opportunity to learn human representations reusable across sensing tasks. However, sparse detections…
来源：arXiv cs.AI · 本地全文 站内详情Co-Evolving Policy and Rubric via Capability Awareness for Open-Ended Generation
Rubric-based reinforcement learning (RL) offers interpretable, fine-grained supervision for aligning large language models (LLMs) on open-ended generation tasks…
来源：arXiv cs.AI · 本地全文 站内详情A-RSI: Adaptive Task Refresh for Zero-Data Multimodal Self-Improvement
Recursive self-improvement requires models not only to acquire useful training experience, but also to decide when their current experience has ceased to be use…
来源：arXiv cs.AI · 本地全文 站内详情CALM: Conflict-Aware Lifecycle Memory Governance for Long-Horizon Language Agents
A memory can be outdated for present-day reasoning yet indispensable for reconstructing the past. Relevance-based retrieval overlooks this tension: semantic rel…
来源：arXiv cs.AI · 本地全文 站内详情智能驾驶进入物理AI时代？7位行业嘉宾给出最新判断
10月26日，第八届智能驾驶大会暨2026环秀湖物理AI产业发展推介会在苏州相城举行。 上一届，车路云一体化、智能驾驶出海和无人驾驶商业化是讨论重点，而到了今年，大会的讨论边界进一步从智能驾驶向物理AI延伸。 世界模型、强化学习、端侧智能、虚拟仿真、Robotaxi之外，机器人、低空飞行器等不同形态的物理智能开始出现在…
来源：雷锋网 · 本地全文 站内详情