AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsIs this machine playing?
arXiv:2610.07130v1 Announce Type: new Abstract: We placed a modern AI coding assistant in an unintended role: as the mind of a body on an unknown digital island. With only a minimal instruction mentioning no specific tas…
- arXiv cs.AIresearchSim-to-Real Transfer of Vision-Language Navigation in Continuous Environments Using an Ackermann-Steered Mobile Robot
arXiv:2610.07192v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) enables robots to navigate through environments using natural language instructions, making human-robot interaction intuitive. Traditional…
- arXiv cs.AIresearchEnergy-Conditioned Noise Schedule and Whitening for Spectral Diffusion
arXiv:2610.07206v1 Announce Type: new Abstract: This paper introduces an energy-adaptive noise scheduling and whitening strategy for transform-domain diffusion models. Existing spectral diffusion methods account for the…
- arXiv cs.AIresearchCascadia: Resident 975B MoE Inference on Eleven AI PCs
arXiv:2610.07219v1 Announce Type: new Abstract: Mixture-of-experts models make nearly trillion-parameter capacity accessible with sparse per-token computation, provided that the serving system can distribute the weights…
- arXiv cs.AIresearchSPECTRUM: Proximal Spectral Modulation for Looped Self-Distillation
arXiv:2610.07237v1 Announce Type: new Abstract: A model that learns from its own outputs inherits more than their correctness: it inherits which solutions it produces. We formulate Looped Self-Distillation, a self-evolut…
- arXiv cs.AIagentsCan Semantic Geometry Teach an AI Judgement?
arXiv:2610.07249v1 Announce Type: new Abstract: How can an AI agent determine what rules to follow? One rule permits an action. Another imposes a condition, exception, or conflicting obligation. Deterministic systems can…
- arXiv cs.AIagentsInternalizing Agent Experience into Diffusion Model Weights via On-Policy Context Distillation
arXiv:2610.07250v1 Announce Type: new Abstract: Wrapping an image generation model in an agentic harness can effectively boost Text-to-Image task performance: the harness can leverage memory, skills, workflow orchestrati…
- arXiv cs.AIagentsMemMux: Runtime Verification and Honest Resource Attribution for Fleets of Parallel Coding Agents
arXiv:2610.07257v2 Announce Type: replace Abstract: Developers increasingly run a fleet of coding agents side by side on one workstation. Terminal multiplexers like tmux and a new generation of agent managers were built…
- arXiv cs.AIagentsVerifying Coordination in Parallel Coding Agents: NP-Bench and a Scheduling Planner
arXiv:2610.07261v1 Announce Type: new Abstract: A team of coding agents can look fine agent by agent yet fail as a team: each passes its own tests while the merged result is broken, and single-agent evaluation never catc…
- arXiv cs.AIresearchDoes the Model Use the Feature? Separating Steering from Mechanism in LLMs
arXiv:2610.07270v1 Announce Type: new Abstract: Internal features in LLMs are often interpreted as mechanisms when they track a concept and their manipulation changes a related behavior. Yet steering can push a feature f…
- arXiv cs.AIagentsA Trust Layer for Agent Evaluation
arXiv:2610.07274v1 Announce Type: new Abstract: Deterministic benchmark scores show that an agent received credit, but not whether that credit was earned, reported honestly, or would hold on a second run. We introduce a…
- arXiv cs.AIagentsThe Right Memory in the Wrong Context: Verifying Retrieval Admissibility in Long-Term Agent Memory
arXiv:2610.07309v1 Announce Type: new Abstract: Long-term-memory agents can retrieve relevant information that is inadmissible for the current request because it belongs to another principal, violates policy, or reflects…
- arXiv cs.AIagentsUnderstanding and Mitigating Inference-Time Overreliance Using Agentic Memory
arXiv:2610.07311v1 Announce Type: new Abstract: Agentic memory allows LLM agents to reuse past experience, yet retrieved memories can also distort inference even when they are benign, correctly stored, and appropriately…
- arXiv cs.AIresearchRule-Based Languages for Neurosymbolic AI
arXiv:2610.07313v1 Announce Type: new Abstract: Logic programming is increasingly used as the symbolic component of neurosymbolic AI systems. We survey the main rule-based languages in this setting, namely Datalog, answe…
- arXiv cs.AIresearchRationale-Guided Policy Optimization: Learning to Reason with Adaptive Rationale Scaffolding
arXiv:2610.07342v1 Announce Type: new Abstract: On-policy reinforcement learning has become a central paradigm for improving the reasoning abilities of large language models. However, its effectiveness is often limited b…
- arXiv cs.AIresearchTrajectory-Retrieval Speculative Decoding: When Does a Model's Own History Help?
arXiv:2610.07350v1 Announce Type: new Abstract: Long chain-of-thought reasoning increases sequential decoding cost while creating a growing history of potentially reusable continuations. We investigate when this history…
- arXiv cs.AIresearchEvaluating Escalation Signals for LLM Routing: Targets, Controls, and Five Ways to Fool Yourself
arXiv:2610.07354v1 Announce Type: new Abstract: Deciding when to escalate a query from a small language model to a larger one requires a cheap signal that predicts, before the large model is called, whether escalating wo…
- arXiv cs.AIagentsEvaluate the Stack, Not the Layer: Do Deterministic and LLM Gates for Agent Actions Fail Independently?
arXiv:2610.07359v2 Announce Type: replace Abstract: Runtime gates for agent tool calls are stacked on the assumption that their errors multiply. We test it on 1,119 labelled agent actions from three corpora, without an a…
- arXiv cs.AIagentsMemCo: Memory-Centric Collaboration for Generalizing LLM Agents to Unseen Environments
arXiv:2610.07376v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly operate in interactive environments, where they need to make sequential decisions through observation, action, and feedback.…
- arXiv cs.AIresearchDefense-in-Depth for LLMs: Evaluating Memory Gates Against Activation-Induced and Memory-Induced Sycophancy
arXiv:2610.07403v1 Announce Type: new Abstract: Long-term memory allows Large Language Models (LLMs) to maintain personalized context across interactions, but retrieved user history can induce memory-induced sycophancy,…
- arXiv cs.AIresearch2d-fet-bench: from spatial reasoning to fet design on flakes
arXiv:2610.07423v1 Announce Type: new Abstract: Field-effect transistor (FET) layouts on exfoliated two-dimensional flakes are typically drawn by hand for each flake, placing contacts and gates to match its position and…
- arXiv cs.AIresearchAdaptive Gait Biofeedback With Participant-Held-Out Modeling and Participant-Specific Updating in Chronic Ankle Instability
arXiv:2610.07428v2 Announce Type: replace Abstract: Adaptive gait biofeedback may support repeated practice in chronic ankle instability, but its evaluation must address model performance and human response. We evaluated…
- arXiv cs.AIresearchWhen Does AI Supervision Help? A Role-Aware Study of Network Fraud Decision Management with Blockchain Auditability
arXiv:2610.07434v1 Announce Type: new Abstract: When does a second artificial intelligence (AI) component improve a primary network-fraud decision rather than add operational burden? We study this question through a role…
- arXiv cs.AIagentsAuditable Claims about AI Agents
arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe to deploy. Article 12…
- arXiv cs.AIresearchCOMPASS: Finding Where Reasoning Lives in Language Models
arXiv:2610.07469v2 Announce Type: replace Abstract: Explicitly eliciting reasoning substantially improves LLM performance. Existing approaches require a predefined characterization of reasoning, whether through CoT promp…
- arXiv cs.AIagentsPsyCIDRA: A Dual-Agent Framework for Psychiatric Interviewing and Diagnostic Reasoning
arXiv:2610.07473v1 Announce Type: new Abstract: Large language models show promise in clinical reasoning, but psychiatric interviewing requires guiding an evolving conversation. Their ability to carry out this interactiv…
- arXiv cs.AIresearchIn With the Old: Enhancing 'Classical' Document Automation with Generative AI
arXiv:2610.07480v1 Announce Type: new Abstract: Software-based legal assistance systems have leveraged many different forms of knowledge representation and reasoning. This article explores how document automation service…
- arXiv cs.AIresearchDoes Muon Need Fine-Grained Spectral Shaping?
arXiv:2610.07497v1 Announce Type: new Abstract: Muon combines current and past gradients into matrix momentum. For $M=U\Sigma V^\top$, the idealized polar update $Q=UV^\top$ gives every singular direction the same weight…
- arXiv cs.AIresearchMARS: Multi-resolution Adaptive Routing for Sequential Recommendation
arXiv:2610.07505v1 Announce Type: new Abstract: Long-history recommenders often compress each user's history into a compact, candidate-independent memory that is cached and reused to score large candidate pools. We show…
- arXiv cs.AIagentsOn Open-Ended Information Seeking for Information Elicitation Agents
arXiv:2610.07509v1 Announce Type: new Abstract: Information elicitation is an open-ended information-seeking problem in which an interaction can unfold in many potentially valuable directions, requiring an elicitor to co…
- arXiv cs.AIresearchFrom Local Evidence to Safety Verdicts: Causal Tracing in Vision-Language Models
arXiv:2610.07514v1 Announce Type: new Abstract: A vision-language model may need to combine an image with a prompt to recognize a safety risk that neither reveals alone. Where does this joint safety judgment become acces…
- arXiv cs.AIagentsGrounding What Shapes the Plan: Rethinking Groundedness for Physical Intelligence in Autonomous Driving
arXiv:2610.07521v1 Announce Type: new Abstract: Driving models increasingly ground reasoning in causal relations, spatial structure, perceptual evidence, and predicted futures. These advances make reasoning more faithful…
- arXiv cs.AIresearchA Systematic Investigation of Bias in Large Language Models for Advertising Relevance
arXiv:2610.07544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to judge how well an advertisement matches a query, but the fairness of these judgments has received limited attention. W…
- arXiv cs.AIagentsDecoupled Multi-Agent Orchestration
arXiv:2610.07556v2 Announce Type: replace Abstract: Learned orchestration can automatically construct effective language-model multi-agent systems, but existing approaches couple planning to fixed worker pools and train…
- arXiv cs.AIresearchNavigating Route Latent Space for Synthesizable Molecular Design
arXiv:2610.07560v1 Announce Type: new Abstract: Goal-directed molecular design has advanced rapidly, yet a substantial proportion of designed molecules remain difficult to synthesize in practice, limiting their real-worl…
- arXiv cs.AIagentsUnanimously Wrong: Certified Abstention from How Medical LLM Consensus Forms
arXiv:2610.07570v1 Announce Type: new Abstract: In clinical practice, agreement among independent experts is treated as evidence of reliability, and multi-round consensus has become a core mechanism of agentic medical qu…
- arXiv cs.AIagentsCooperating with Future Collaborators: Multi-Agent RL under Staggered Participation
arXiv:2610.07578v1 Announce Type: new Abstract: In cooperative Multi-Agent Reinforcement Learning (MARL), agents are often trained under concurrent participation, while in many tasks some agents act earlier and leave tas…
- arXiv cs.AIresearchLOGIC: An LLM Benchmark for Intent-Grounded Change Impact in Aerospace Electrical Systems
arXiv:2610.07580v1 Announce Type: new Abstract: Aerospace electrical-design revisions can contain multiple genuine changes, although an engineering request may authorize only a subset. Propagating every detected differen…
- arXiv cs.AIresearchRepresentation Bias, Correction Transfer, and Resolution Sensitivity in Three-Dimensional Mitochondrial Morphometry
arXiv:2610.07582v1 Announce Type: new Abstract: Quantitative imaging pipelines can produce precise but systematically different measurements of the same object. We present an empirical reliability assessment of three-dim…
- arXiv cs.AIagentsPersonal-Agent Mediated Recommendation with Cross-Platform User History
arXiv:2610.07588v1 Announce Type: new Abstract: Modern recommendation is shifting from platform-centric personalization toward user-governed personalization, where a personal LLM agent can act on the user's behalf across…
- arXiv cs.AIresearchLSC-DPO: Learning-Signal-Controlled Direct Preference Optimization
arXiv:2610.07592v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) has become a standard reward-model-free approach for aligning language models with preference data. However, as the scaled preference m…
- arXiv cs.AIresearchBeyond Scalar IoU: Structured Verification from Rollout Groups for Video Temporal Grounding
arXiv:2610.07601v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a natural framework for adapting pretrained models to video temporal grounding, where generated temporal inte…
- arXiv cs.AIresearchVALSE: Vertical Adaptive Layer Skipping for Efficient Inference in Large Language Models
arXiv:2610.07606v1 Announce Type: new Abstract: This paper establishes a theoretical framework for vertical adaptive layer skipping, proving three foundational results: (i) an Expected FLOPs formula (theorem 2) giving a…
- arXiv cs.AIagentsBioStudyBench: Evaluating Agents on Post-Cutoff Biomedical Studies
arXiv:2610.07614v1 Announce Type: new Abstract: We evaluate whether AI agents can match the reported findings of published biomedical studies using public data. Existing evaluations do not consistently separate analysis…
- arXiv cs.AIresearchExplore, Then Commit: Measurement-Efficient Scientific Law Discovery with Language Models
arXiv:2610.07620v1 Announce Type: new Abstract: Scientific law discovery requires selecting measurements and converting evidence into a governing equation. We evaluate an explore-then-commit protocol in which a large lan…
- arXiv cs.AIresearchLearning to Outgrow a Theory: Experimental Discovery Beyond the Initial Hypothesis Space
arXiv:2610.07627v1 Announce Type: new Abstract: Scientific discovery systems typically optimize experiments within a fixed hypothesis space. This creates a failure mode when all available candidates omit the same missing…
- arXiv cs.AIresearchMeasuring climate backlash in Twitter and Reddit archives: Lexical definitions, recorded responses and participant turnover
arXiv:2610.07634v1 Announce Type: new Abstract: Social media archives are often used to study resistance to climate action, but words, response counters and observed participants do not measure the same social process. W…
- arXiv cs.AIresearchLearning Explainable Representations of Complex Game-playing Strategies
arXiv:2610.07638v1 Announce Type: new Abstract: As part of learning to play complex games, human players develop develop abstractions for concepts and strategies of gameplay consistent with game rules to improve their pe…
- arXiv cs.AIagentsTowards the Automatic Synthesis of Interpretable Chess Tactics
arXiv:2610.07640v1 Announce Type: new Abstract: State-of-the-art reinforcement learning agents are capable of outperforming human experts at games like chess, Go and StarCraft II. These agents do not simply take advantag…
- arXiv cs.AIresearchMatching Object or Relation? Tracing Abstract Reasoning Inside VLMs
arXiv:2610.07646v1 Announce Type: new Abstract: Vision Language Models (VLMs) excel on visual benchmarks but fail systematically on tasks requiring abstract reasoning. Existing benchmarks document this failure but cannot…