AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsGood Judgment, Bad Advice: Decision-Model Controllers Raise Agent Cost Without Improving Success
arXiv:2610.24649v1 Announce Type: new Abstract: Agent scaffolds increasingly delegate small decisions (whether to stop, verify, or change approach) to cheaper models. We ask whether a typed decision model, Jev 1.13, cons…
- arXiv cs.AIagentsCan AI agents make law? Evaluating AI legal relevance and creativity
arXiv:2610.24661v1 Announce Type: new Abstract: Large language models, the artificial intelligence (AI) systems behind modern chatbots, are trained on vast amounts of legal text, but can they build on it to write law for…
- arXiv cs.AIresearchFrom Prediction to Action: Population Health World Model for Digital Medicine
arXiv:2610.24662v2 Announce Type: replace Abstract: Digital medicine now captures data that traces individual health trajectories and reveals population health dynamics through electronic health records, claims, remote m…
- arXiv cs.AIresearchMM-LeJEPA: Correlated Gaussian Regularization for Multimodal Joint-Embedding Predictive Architectures
arXiv:2610.24681v1 Announce Type: new Abstract: LeJEPA derives an isotropic Gaussian embedding target by minimizing, under its task assumptions, a Fisher information criterion that controls the task-averaged squared pred…
- arXiv cs.AIresearchVerifying Human-Written Reasoning References
arXiv:2610.24690v1 Announce Type: new Abstract: Evaluating the reasoning of AI systems often relies on human-written reasoning chains as references, yet the logical support for their individual steps is rarely verified.…
- arXiv cs.AIresearchSpherical Physics-informed Neural Operator with Multi-scale Coupling for Meteorological Downscaling
arXiv:2610.24708v1 Announce Type: new Abstract: Meteorological downscaling is crucial for high-resolution regional climate forecasting and disaster early warning. While neural operators have emerged as a promising paradi…
- arXiv cs.AIresearchSQuIREL: A Context-Relative Framework for Measuring Entity Richness in Wikidata
arXiv:2610.24709v1 Announce Type: new Abstract: Wikidata is a large, heterogeneous knowledge graph and applying data quality metrics requires context-specific approaches. The "richness" quality metric is currently under-…
- arXiv cs.AIagentsNeuro-Inspired Inhibitory Message Passing for Accurate and Token-Efficient Multi-Agent Reasoning
arXiv:2610.24718v1 Announce Type: new Abstract: Multi-agent systems promise to solve problems by bringing together information beyond the reach of any individual agent. Retrieval and tool use can distribute this informat…
- arXiv cs.AIagentsWhere Natural Language Ends in Agents: Executable Skill Composition with MetaSkill
arXiv:2610.24723v1 Announce Type: new Abstract: Agent Skills express open-ended task knowledge in natural language, but composing them requires persistent execution order and upstream-output handoffs. We propose selectiv…
- arXiv cs.AIagentsCan LLM Agents Resolve Service Failures? Simulating Multi-Turn Complaint Handling under Information Asymmetry
arXiv:2610.24733v1 Announce Type: new Abstract: LLM agents are widely adopted in service chatbots for rule-guided support and information access, yet emotionally demanding complaint handling still relies heavily on human…
- arXiv cs.AIresearchToward Collective Model Intelligence: Characterizing and Coordinating Models
arXiv:2610.24739v1 Announce Type: new Abstract: Independently developed AI models accumulate diverse and complementary capabilities, but a growing model collection does not automatically realize Collective AI. Addressing…
- arXiv cs.AIresearchAre We Evaluating VLM Token Pruning Right? Looking Beyond Accuracy and Token Count
arXiv:2610.24740v1 Announce Type: new Abstract: Visual token pruning aims to reduce inference cost while preserving the capabilities of the original VLM. Yet existing evaluations rely on aggregate task accuracy and retai…
- arXiv cs.AIagentsReTRACE: Feedback-Guided LLM Agent in a Chemistry Harness for Retrosynthesis Planning
arXiv:2610.24744v1 Announce Type: new Abstract: Computer-aided retrosynthesis has advanced through single-step prediction, tree search and route scoring, but complex targets still require judgement over the whole route,…
- arXiv cs.AIagentsDialogMem: Evaluating Dialogue-Grounded Embodied Memory in 3D Environments
arXiv:2610.24767v1 Announce Type: new Abstract: Embodied agents in human-centered environments require memory that integrates what they observe with what humans tell them over time. However, existing embodied memories ar…
- arXiv cs.AIresearchIndustrialCAD-1400: Benchmarking Detailed Industrial Assemblies from Text
arXiv:2610.24789v1 Announce Type: new Abstract: Industrial assemblies require more than a recognizable shape: functional parts, interfaces, dimensions and service features must satisfy a detailed request together. We int…
- arXiv cs.AIresearchMedical Fine-Tuning Reshapes, Not Reduces, Patient-Facing AI Risk: A Rubric-Based, LLM-Judge Evaluation Framework
arXiv:2610.24807v1 Announce Type: new Abstract: Patient-facing medical question answering with large language models (LLMs) is moving from research demonstrations to production deployments, yet evaluation remains anchore…
- arXiv cs.AIagentsTeaching Code Agents to Ask Without Leaking Private Code
arXiv:2610.24824v1 Announce Type: new Abstract: Local coding agents can extend their reach by consulting a stronger cloud model. Such consultations, however, often expose the repository's private identifiers, file paths,…
- arXiv cs.AIresearchPattern-Driven Evaluation of LLM Code Optimization: Isolating Compiler-Transcendent Semantic Reasoning
arXiv:2610.24835v1 Announce Type: new Abstract: Existing evaluations of LLM-based code optimization primarily measure end-to-end speedup, obscuring whether a model actually performs the intended optimization. For compile…
- arXiv cs.AIagentsBellman Language Models: Solving the Recurring Decisions of LLM Agents
arXiv:2610.24871v1 Announce Type: new Abstract: A general observation in agentic workflows, especially bounded ones, is that the decision space of the LLM, when we separate a decision from generation, starts approaching…
- arXiv cs.AIagentsThe One-Pixel of Reasoning: One Truthful Relation Is Enough to Mislead LLM Agents
arXiv:2610.24873v1 Announce Type: new Abstract: Can one sentence manipulate an agent's belief by targeting a single implicit warrant linking evidence to a conclusion? In this paper, we introduce the one-relation attack (…
- arXiv cs.AIagentsHybridResearcher: Bridging the Structured-Unstructured Boundary for Deep Research Agents
arXiv:2610.24899v2 Announce Type: replace Abstract: While LLM agents are increasingly capable of gathering and synthesizing evidence from a single homogeneous source, such as structured tables or unstructured data, real-…
- arXiv cs.AIresearchA Cross-Domain Evaluation of Prompting Techniques for Large Language Models
arXiv:2610.24913v1 Announce Type: new Abstract: Prompt engineering has become a central mechanism for guiding the behavior of Large Language Models (LLMs) across a wide range of reasoning and language understanding tasks…
- arXiv cs.AIresearchMeans-Ends Analysis Helps LLMs Plan in Continuous-State Domains
arXiv:2610.24928v1 Announce Type: new Abstract: LLM planning research has traditionally focused on discrete-state domains, where actions form a finite, enumerable set. Existing LLM planning frameworks largely assume acti…
- arXiv cs.AIresearchLowNet: Looped Wavelet Neural Networks with 24 Learnable Parameters for Solving Poisson Equations
arXiv:2610.24941v1 Announce Type: new Abstract: Poisson equations frequently appear in various fields, such as mathematics, physics and informatics. Solving Poisson equation, however, is challenging. Traditional methods…
- arXiv cs.AIagentsMemPrice: Online Memory Allocation via Adaptive Pricing for Long-Horizon Agents
arXiv:2610.24955v1 Announce Type: new Abstract: Long-horizon LLM agents face a fundamental allocation problem as interaction histories grow: which information to retain, how much context to devote to it, and at what gran…
- arXiv cs.AIresearchRevealing what benchmark scores hide: Jointly measuring the breadth and reliability of LLM capabilities using accessibility profiles
arXiv:2610.24957v1 Announce Type: new Abstract: Language model benchmarks assign each question a single outcome from one fixed wording, even though the same underlying request can be expressed in many equivalent ways. We…
- arXiv cs.AIagentsCoworkEnv: Synthesizing Training Environments for Long-Horizon Cowork Agents
arXiv:2610.24960v1 Announce Type: new Abstract: AI coworkers must coordinate tools, communicate across turns, and act on changing workspace state while respecting workflow constraints. Constructing training experience fo…
- arXiv cs.AIresearchTowards Human-AI Complementarity for AI Safety
arXiv:2610.24969v2 Announce Type: replace Abstract: Safely overseeing AI is increasingly challenging for the humans doing it, as they must evaluate longer and more complex outputs with every new model generation. To miti…
- arXiv cs.AIresearchCorrectRTL: Boost RTL Generation Quality Through Automated Self-Correction with Instruction Decomposition
arXiv:2610.24977v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong promise in specification-to-RTL generation. Among the explorations, the self-correction paradigm has significantly advanced L…
- arXiv cs.AIresearchVLA-Rolling: Fewer Denoising Steps, Better Control via Adaptive Action Reuse
arXiv:2610.25043v3 Announce Type: replace Abstract: Flow-matching vision-language-action (VLA) models generate an action chunk by iteratively denoising Gaussian noise, but typically execute only a short prefix before rep…
- arXiv cs.AIresearchSteadyThought: Mitigating LLM Under-Thinking via Thought-Level Preference Optimization
arXiv:2610.25045v1 Announce Type: new Abstract: Flexible switching between reasoning trajectories (i.e., thought switching) has significantly enhanced the reasoning capabilities of Large Reasoning Models (LRMs). However,…
- arXiv cs.AIagentsOne Skill Takes Over: Clashing Agent Skills and a One-File Fix
arXiv:2610.25064v1 Announce Type: new Abstract: Agent Skills are instruction files that tell a coding agent how to do one job. Users install skills from many authors, so two skills for the same job can be active at the s…
- arXiv cs.AIagentsDAGLoop: Aligning Method Design with Experimental Feedback in Automated AI Research
arXiv:2610.25089v1 Announce Type: new Abstract: Automated AI research agents aim to improve machine learning methods by iteratively proposing, implementing, and evaluating candidate methods. Existing work uses the outcom…
- arXiv cs.AIagentsToward Agentic Retrieval-Augmented Generation for Enterprise Retail Workflows over Heterogeneous Data Sources
arXiv:2610.25096v1 Announce Type: new Abstract: Enterprise retail workflows require agents to chain evidence across heterogeneous sources, from structured product and order records to unstructured inquiries and reviews,…
- arXiv cs.AIagentsExplore or Confirm? LLM Agents Misallocate Measurements Under Noise
arXiv:2610.25111v1 Announce Type: new Abstract: As model reasoning gets cheaper, the physical experiment becomes the slow and costly step in discovery. Each experiment returns a noisy reading: a high value can mean a goo…
- arXiv cs.AIresearchSpectral Adaptive Graph Transformer for Efficient and Scalable Traffic Forecasting
arXiv:2610.25140v1 Announce Type: new Abstract: Traffic forecasting models based on spectral graph convolution offer an interpretable account of how information is mixed between sensors, but they rely on an eigendecompos…
- arXiv cs.AIagentsMemory, Know Your PLACE: Governing Lifecycle State and Query-Time Eligibility in Persistent-Memory Agents
arXiv:2610.25179v1 Announce Type: new Abstract: Persistent memory turns prior interactions into durable agent state, but existing systems provide limited control over whether that state remains valid and whether it shoul…
- arXiv cs.AIresearchDialogue Generation for Conversational Recommendation Using User Search Interactions and Knowledge Graphs
arXiv:2610.25182v1 Announce Type: new Abstract: Large-scale conversational recommendation datasets typically require manual dialogue construction or annotation. We propose SearCl, which automatically generates conversati…
- arXiv cs.AIagentsBrandEval: A Two-Track Multi-Agent Benchmark for Risk-Sensitive LLM Crisis Communication
arXiv:2610.25208v1 Announce Type: new Abstract: Evaluating LLMs for crisis communication requires more than judging isolated responses, because public feedback and competitor actions can reshape trust over time. Existing…
- arXiv cs.AIagentsBridging Concepts: Multi-Agent Reasoning over Scientific Concept Graphs for High-Impact Research Prediction
arXiv:2610.25281v1 Announce Type: new Abstract: Within a research community, new topics often emerge when previously unconnected concepts are first studied together. We construct scientific concept graphs (SCGs)--domain…
- arXiv cs.AIresearchAligning Language Models with Indigenous Community Cosmovision through Constitutional AI
arXiv:2610.25298v1 Announce Type: new Abstract: Large language models (LLMs) are predominantly trained on corpora that reflect Western, anglophone worldviews. This asymmetry is not neutral: when a model answers questions…
- arXiv cs.AIagentsOutcome-Anchored Credit Reallocation for Agentic Knowledge Graph Question Answering
arXiv:2610.25384v1 Announce Type: new Abstract: Agentic knowledge graph question answering (KGQA) requires large language models (LLMs) to solve complex questions through multi-turn interactions with a knowledge graph (K…
- arXiv cs.AIresearchWhen Form Changes but Logic Doesn't: Building Logic-invariant LLMs through Logical Structure
arXiv:2610.25402v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved strong performance across diverse reasoning tasks, yet it remains unclear whether this performance reflects an understanding…
- arXiv cs.AIresearchStepwise Reasoning Verification: Don't Generate, Classify!
arXiv:2610.25441v1 Announce Type: new Abstract: Verifying the reasoning of large language models is increasingly important as they are applied to complex mathematical and scientific problems. Existing work focuses on lar…
- arXiv cs.AIagentsSystem X: An LLM Decision Model That Replies from Its Own KV Cache
arXiv:2610.25456v1 Announce Type: new Abstract: Decision models return probabilities over supplied options, but a deployed agent may also need to reply in words. The present study introduces System X, a large language mo…
- arXiv cs.AIresearchOn Reasoning Correctness Directions
arXiv:2610.25464v1 Announce Type: new Abstract: We present experimental evidence suggesting that information about whether a model's reasoning is on the right track can be linearly decodable without defining a causally u…
- arXiv cs.AIresearchA failure of Imagination: VLMs fail to use visual representations for text, but self-distillation can help
arXiv:2610.25470v1 Announce Type: new Abstract: Vision-language (VL) models are typically built by fine-tuning a language model to attend to visual features in service of a Visual Question-Answering objective. We ask whe…
- arXiv cs.AIresearchP(Yes): 15$\times$ Improvements via Test-Time Scaling of Decision Models
arXiv:2610.25474v1 Announce Type: new Abstract: Decision models answer typed questions, such as multiple-choice or yes/no questions, with a probability for each option. We add test-time search to frozen decision models,…
- arXiv cs.AIresearchFrom Proposal to Execution: Modeling Interaction Semantics in Shared Autonomy
arXiv:2610.25496v2 Announce Type: replace Abstract: In many human-AI systems, candidate actions are not executed directly but are first evaluated by another decision-making entity under a potentially different objective…
- arXiv cs.AIresearchAssessing the AI Readiness of Construction Datasets: A Multidimensional Operational Framework
arXiv:2610.25499v1 Announce Type: new Abstract: The rapid growth of artificial intelligence (AI) applications in construction has increased the demand for datasets suitable for reliable model development, evaluation, and…