AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsBeyond the Evidence Coherence Trap: Agent-Driven Evidence Selection for Temporally Disordered Fake News Detection
arXiv:2610.36764v1 Announce Type: new Abstract: Fake news undermines public trust and the integrity of online information ecosystems. Temporally disordered fake news is especially elusive because it rearranges factual ev…
- arXiv cs.AIresearchCan LLMs Reliably Grade Olympiad Proofs? A Study of Mathematical Verification with LLMs
arXiv:2610.36767v1 Announce Type: new Abstract: Large Language Models (LLMs) have made remarkable progress on solving competition-level mathematics, yet their ability to verify natural-language mathematical proofs remain…
- arXiv cs.AIagentsBatching the Reflective Optimization Loop: Parallel Proposals Make GEPA Faster and Better
arXiv:2610.36774v1 Announce Type: new Abstract: Reflective text optimization makes agentic systems better, but the optimization loop is itself a resource-hungry workload whose sequential structure leaves parallel evaluat…
- arXiv cs.AIresearchDependency Graphs of Mathematical Arguments: Representation, Structural Measurement, and Proof Review
arXiv:2610.36776v1 Announce Type: new Abstract: We propose a source-grounded framework for representing and measuring mathematical arguments with assistance from large language models. It includes numbered and unnumbered…
- arXiv cs.AIresearchAn Incremental Knowledge-Graph Learner Digital Twin for Evidence-Grounded Early Warning
arXiv:2610.36820v2 Announce Type: replace Abstract: Early-warning models in learning analytics can identify learners at risk of failure or withdrawal, but the resulting alerts are often only weakly connected to inspectab…
- arXiv cs.AIagentsWho Knows What - and What Does It Support? Perspective-Bounded Evidence Calibration for Multimodal Theory of Mind
arXiv:2610.36824v1 Announce Type: new Abstract: Theory of Mind (ToM), the ability to infer others' beliefs, goals, and intentions, is a cornerstone of social intelligence. Multimodal ToM requires inferring an agent's men…
- arXiv cs.AIagentsWhen the Critic Falls Behind: Co-Evolving Rubrics and Harnesses for Continual Agent Self-Improvement
arXiv:2610.36826v1 Announce Type: new Abstract: Autonomous agents increasingly depend on harnesses that govern interaction, memory, tools, and execution around large language models (LLMs). While recent work has begun to…
- arXiv cs.AIresearchConservative Policy Iteration For Zero-Sum POSGs
arXiv:2610.36847v1 Announce Type: new Abstract: Occupancy-state reductions make dynamic programming possible for zero-sum partially observable stochastic games (zs-POSGs). Existing point-based solvers usually optimise a…
- arXiv cs.AIagentsEvolving Agent Teams
arXiv:2610.36848v1 Announce Type: new Abstract: The rapid progress of software engineering agents drives interest in applying them to open-ended problems such as GPU kernel optimization. However, we find that existing co…
- arXiv cs.AIagentsGUI-JEPA: Candidate-Conditioned JEPA Latents as a Fast Action Policy for Mobile GUI Agents
arXiv:2610.36877v1 Announce Type: new Abstract: Mobile GUI agents are typically fine-tuned 7B-scale vision-language models (VLMs) that generate each action as text. However, these VLMs decode every action token by token,…
- arXiv cs.AIagentsRubricAtlas: Mining Type-Level Rubrics from Expert Reports to Evaluate Deep Research Agents
arXiv:2610.36878v1 Announce Type: new Abstract: Deep research agents conduct multi-step Web searches and synthesise retrieved information into analytical reports. Evaluating these outputs requires checking which analyses…
- arXiv cs.AIresearchNoise Steering: Exploiting Wake Steering and Acoustic Directivity for Noise-Constrained Wind Farm Control via Reinforcement Learning
arXiv:2610.36888v2 Announce Type: replace Abstract: Existing noise mitigation strategies for wind farms usually consist in reducing turbines power output, without accounting for the wake interactions between them and the…
- arXiv cs.AIresearchNatural Hard-Negative Mining from Positives for Instruction-Following Retrieval
arXiv:2610.36900v1 Announce Type: new Abstract: Instruction-following information retrieval (IFIR) requires retrievers to rank documents by both a query and its instance-specific instructions, yet instruction-conditioned…
- arXiv cs.AIagentsVision-Language Agents Can Learn in Their Own Latent Worlds
arXiv:2610.36925v1 Announce Type: new Abstract: Learning from experience is essential for building the next generation of agents that continually expand their capabilities. Pretrained vision-language models (VLMs) alread…
- arXiv cs.AIresearchDo bots feel bad? Assessing empirical evidence for functional valence in LLMs
arXiv:2610.36962v1 Announce Type: new Abstract: Do LLMs have valenced states, i.e. states that feel pleasant or unpleasant? Recent empirical work has claimed to show that LLMs possess functional valenced states (e.g. ``f…
- arXiv cs.AIagentsProactive Memory for Event-Driven LLM Agents
arXiv:2610.36967v1 Announce Type: new Abstract: Proactive LLM agents anticipate service opportunities from ongoing observations and accumulated history. Existing approaches emphasize recent context or retrieval of relate…
- arXiv cs.AIagentsAutoVend: Benchmarking LLM Agents on Long-Horizon Autonomous Vending Operations
arXiv:2610.36980v1 Announce Type: new Abstract: Large language model (LLM) agents are extending agent-mediated commerce on the Web from shopping for consumers to operating businesses for sellers. In online-to-offline (O2…
- arXiv cs.AIresearchSpectRAG: Weighted Chunk Graphs for Token-Budgeted Context Selection in Multi-Hop Retrieval-Augmented Generation
arXiv:2610.36991v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) systems ground large language models (LLMs) by retrieving external evidence and conditioning generation on the retrieved context. A…
- arXiv cs.AIresearchGuided-RLVR: Guided Exploration in Reinforcement Learning with Verifiable Rewards
arXiv:2610.37041v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has shown strong empirical gains in improving the reasoning ability of large language models (LLMs) on tasks such as m…
- arXiv cs.AIresearchAI-Assisted Discovery of CNOT Decompositions for Quantum Permutations on Constrained Topologies
arXiv:2610.37045v1 Announce Type: new Abstract: Efficient quantum circuit compilation is challenging for quantum computers, where limited qubit connectivity can introduce substantial overhead in the implementation of log…
- arXiv cs.AIresearchCorrectness Conditioning as Selection in Chain-of-Thought Faithfulness Evaluation
arXiv:2610.37070v1 Announce Type: new Abstract: Restricting chain-of-thought (CoT) faithfulness evaluation to correctly answered instances changes the population being measured. We study this selection step in a seven-va…
- arXiv cs.AIagentsOpenGray: a benchmark for evaluating the decisions of radiotherapy planning agents
arXiv:2610.37081v1 Announce Type: new Abstract: Background and purpose: Radiotherapy planning agents based on large language models (LLMs) decide when to submit a plan or request review but are evaluated mainly by dose.…
- arXiv cs.AIresearchProspector: learning a compact graph traversal policy for scientific reasoning
arXiv:2610.37121v1 Announce Type: new Abstract: Scientific reasoning in specialized engineering fields depends on knowledge scattered across the literature, often proprietary and absent from frontier LLM training data. I…
- arXiv cs.AIresearchSFE-O: An Ontology for Knowledge-Grounded AI in Supercritical CO$_2$ Biomass Extraction and Fractionation
arXiv:2610.37123v1 Announce Type: new Abstract: Supercritical CO$_2$ extraction (CO$_2$-SFE) offers a sustainable route for recovering high-value compounds from biomass while limiting the use of conventional organic solv…
- arXiv cs.AIagentsWorkFactory: Turning Professional Intents into Executable Work for Scalable Agent Training
arXiv:2610.37161v1 Announce Type: new Abstract: Scaling supervised training for working agents requires diverse professional tasks that yield reliable expert demonstrations. However, missing or inconsistent task informat…
- arXiv cs.AIagentsLiveSearch: Questions as Executable Verifier Code for a Live Benchmark of Professional-Source Financial Search Agents
arXiv:2610.37166v1 Announce Type: new Abstract: In finance, the answer that matters is usually the current one: prices, rates, and disclosures hold only as of a given day, so retrieving up-to-date facts is a core capabil…
- arXiv cs.AIresearchR\`enyi-Regularized Flow-Based Variational Inference for Bayesian Calibration
arXiv:2610.37169v1 Announce Type: new Abstract: Variational inference with normalizing flows provides a flexible posterior approximation for Bayesian model calibration, but struggles when the posterior has several modes…
- arXiv cs.AIagentsDoes Your Generalist Skill Optimizer Really Incentivize Agentic Tasks? Rethinking Skill Optimization via Bipartite Attribution
arXiv:2610.37201v1 Announce Type: new Abstract: Skill optimizers adapt an agent to long-horizon tasks, such as repairing a terminal environment, by rewriting its skill, a natural-language procedure in its context, and ke…
- arXiv cs.AIresearchGraphRAGProv: GraphRAG Meets How-Provenance
arXiv:2610.37237v1 Announce Type: new Abstract: GraphRAG systems often use knowledge graphs to retrieve relevant context for an LLM that produces the final answer. That makes answers more inscrutable and therefore less a…
- arXiv cs.AIagentsGrounding LLM Agents in Business Processes: Process-Aware Knowledge Graphs for Reliable Multi-Step Service Invocation
arXiv:2610.37242v1 Announce Type: new Abstract: Large language model (LLM) agents that call enterprise APIs must select the correct endpoints, follow process order, use valid payload keys, and choose coded values from pr…
- arXiv cs.AIresearchTCM-DiagCommit: A TCM-SD-Derived Benchmark for Evidence-Conditioned Syndrome Selection and Commitment
arXiv:2610.37243v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) syndrome differentiation is usually evaluated as static final-label selection over complete clinical records. This setting hides three di…
- arXiv cs.AIresearchRPSD: Retrieval-Privileged On-Policy Self-Distillation with Optimal Transport
arXiv:2610.37281v1 Announce Type: new Abstract: Sequential recommendation predicts a user's next interaction from historical behavior. Recent LLM-based methods recast this task as generative recommendation and increasing…
- arXiv cs.AIresearchReForest: Interpretability Meets Reasoning in Isolation Forest
arXiv:2610.37316v1 Announce Type: new Abstract: Statistical anomaly detection methods like Isolation Forest are efficient but suffer from a critical semantic gap. They identify numerical rarities but fail to understand t…
- arXiv cs.AIagentsAligning Institutional Power and Operational Ability
arXiv:2610.37342v1 Announce Type: new Abstract: To be socially sustainable, Agentic AI systems require normative designs that align responsibilities with the ability to fulfil them. Identifying incongruences such as unsa…
- arXiv cs.AIresearchUncovering Why LLMs Fail: From Internal Mechanisms to Adversarial Reasoning Trajectories
arXiv:2610.37369v2 Announce Type: replace Abstract: Large language models (LLMs) are usually evaluated by final-output correctness or safety, yet an endpoint label does not reveal how a failure develops throughout the re…
- arXiv cs.AIagentsAgent-Conditioned Routing: Diverse Reasoning Paths Within One Frozen Model
arXiv:2610.37375v1 Announce Type: new Abstract: Generating several solutions can expose alternative methods, but additional trajectories often paraphrase one dominant approach. We investigate whether the conditional capa…
- arXiv cs.AIagentsClearing the FoG: Training KG Agents to Retrieve the Evidence Behind Their Answers
arXiv:2610.37405v1 Announce Type: new Abstract: Large language models (LLMs) can answer many factual questions correctly, but a correct answer is not necessarily a supported one. For an LLM agent, a knowledge graph (KG)…
- arXiv cs.AIagentsConstraining the Commit Boundary: A DIO/ODI-Informed Authorization Guardrail for Agentic Entity Resolution
arXiv:2610.37407v1 Announce Type: new Abstract: Agentic Entity Resolution (ER) systems iteratively plan actions, retrieve evidence, revise hypotheses, and propose graph mutations. An erroneous identity hypothesis may con…
- arXiv cs.AIresearchBeyond the Readout: A Latent Numerical Frame Shared Across Modality and Operation
arXiv:2610.37422v1 Announce Type: new Abstract: When a multimodal model computes 17+35 from text or 91-39 from a rendered image, it produces the same answer, 52. Does it use one internal concept of number for both, or se…
- arXiv cs.AIagentsM4Bench: Evaluating Procedural Specification for Clinical EHR Derivation Agents
arXiv:2610.37459v1 Announce Type: new Abstract: Clinical research over electronic health records depends on derived variables whose definitions sit outside the schema, in item codes, time windows, missingness rules, and…
- arXiv cs.AIagentsConcordat: Typed Sessions for LLM Agents
arXiv:2610.37461v2 Announce Type: replace Abstract: Agents built on large language models are increasingly allowed to take consequential actions: cancelling bookings, issuing refunds, changing accounts. The rules that go…
- arXiv cs.AIagentsFrom Interaction to Capability: Task Advancement as State and Supervision for GUI Agents
arXiv:2610.37482v1 Announce Type: new Abstract: GUI memory should preserve the results of past actions and learn reusable operations. This is difficult in long-horizon workflows, where agents must use information across…
- arXiv cs.AIagentsTeamGym: A Gym for Team Decision-Making by AI Agents with Distributed Information
arXiv:2610.37571v1 Announce Type: new Abstract: Many real-world decisions require teams to integrate information distributed across participants. Yet AI agents are still primarily trained and benchmarked in isolation. We…
- arXiv cs.AIresearchTimestral
arXiv:2610.37585v1 Announce Type: new Abstract: We introduce Timestral, a family of four time series foundation models for probabilistic forecasting, with 5M, 28M, 123M, and 209M parameters. Timestral sets a new state of…
- arXiv cs.AIresearchRare, Relevant, and Still Wrong: How Memory Fails LLM Group Decisions
arXiv:2610.37624v1 Announce Type: new Abstract: When an LLM group's discussion is compressed into a short memory for a final decision maker, what should the memory keep? Two natural heuristics keep the rarest claims or t…
- arXiv cs.AIresearchWhat Improves During Pretraining? Tracking Knowledge Acquisition with Point-in-Time Models
arXiv:2610.37631v1 Announce Type: new Abstract: Language models pretrained on web corpora collected over multiple years learn both general and domain-specific knowledge. How these different kinds of knowledge are learned…
- arXiv cs.AIresearchKPPax: preprocess differentiable kinetic ODE for machine learning in atmospheric chemistry
arXiv:2610.37655v1 Announce Type: new Abstract: Atmospheric chemical mechanisms are commonly distributed in the language of the Kinetic PreProcessor (KPP), which generates efficient Fortran or C code but does not fit int…
- arXiv cs.AIresearchASTROLABE: A 3D Particle-Level Surrogate for Cosmology Simulation with Physical Flow Matching
arXiv:2610.27068v1 Announce Type: cross Abstract: The microphysics of dark matter (DM) is imprinted on cosmological structure across an enormous dynamic range. Nonlinear cosmological observables are most reliably modeled…
- arXiv cs.AIresearchscPyviewer: a Python-native interactive viewer from AnnData single-cell data
arXiv:2610.35890v1 Announce Type: cross Abstract: Motivation: Interactive web tools enabling non-programmers to explore single-cell datasets, embeddings, gene expression, metadata, and marker genes are standard laborator…
- arXiv cs.AIresearchBeyond Greenwashing: Algorithmic Resilience and the Non-Linear Governance Premium in Sovereign Capital Flows
arXiv:2610.35895v1 Announce Type: cross Abstract: Despite the proliferation of sovereign Environmental, Social, and Governance (ESG) metrics, traditional linear macro-financial models systematically misprice Foreign Dire…