AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsVERA: Scaling Verifiable Environments for Agentic co-Evolution
arXiv:2610.05923v1 Announce Type: new Abstract: Competent agents need precise and verifiable environments, such as sandboxes that are resumable at any stage and evolve from observable evidence. However, most long-horizon…
- arXiv cs.AIagentsProcess Constitutions and Process Stewards: Towards the Next Generation of BPM for Agentic Organizations
arXiv:2610.05942v1 Announce Type: new Abstract: Business Process Management (BPM) was built on a foundational assumption that organizations are populated primarily by human actors whose work can be made visible, governab…
- arXiv cs.AIagentsOntoInk: Interactive Ontology Visualization, Validation, and Reasoning
arXiv:2610.05945v1 Announce Type: new Abstract: Ontology documentation, visualization, and validation are usually carried out with separate tools. This split workflow slows down development and makes knowledge transfer h…
- arXiv cs.AIresearchGrounded Joint-Attention Other-Play for Zero-Shot Coordination
arXiv:2610.06025v1 Announce Type: new Abstract: Joint attention - the human ability to share a common visual or cognitive focus with others - enables a meeting of minds that lets us coordinate even with unfamiliar partne…
- arXiv cs.AIagentsRocketAgent: A Long-Horizon Engineering Agent for Multidisciplinary Design of Liquid-Rocket Thrust Chambers
arXiv:2610.06044v2 Announce Type: replace Abstract: Liquid-rocket thrust-chamber design involves interdependent analyses in which downstream constraints can require earlier design decisions to be revisited. Managing thes…
- arXiv cs.AIagentsBenchmarking Jailbreak Guardrails for Embodied Agents
arXiv:2610.06122v1 Announce Type: new Abstract: Embodied agents powered by large language models and vision-language models are increasingly deployed in physical environments, but jailbreak attacks can induce these agent…
- arXiv cs.AIresearchOn Impact of Loss Function on the Performance of Neural Networks in Melanoma Diagnosis
arXiv:2610.06139v1 Announce Type: new Abstract: Melanoma is the deadliest type of skin cancer, whose early diagnosis is crucial for patients' survival. Image classification using deep learning models has shown promising…
- arXiv cs.AIresearchImpact of Data Augmentation on Confidence Calibration in Melanoma Classification
arXiv:2610.06146v1 Announce Type: new Abstract: Accurately quantifying the predictive uncertainty or improving model calibration plays an important role in medical image classification, in particular in melanoma diagnosi…
- arXiv cs.AIresearchMS-Exam-Gen: An Automatic Benchmark Construction Toolkit for Evaluating LLMs on Multiple Sclerosis-MRI Imaging Knowledge
arXiv:2610.06170v2 Announce Type: replace Abstract: Biomedical large language model (LLM) evaluation requires auditable assessment of narrow, evolving, source-grounded subspecialty knowledge. Multiple sclerosis MRI (MS-M…
- arXiv cs.AIresearchAuditable Clinical Timeline Reconstruction with Provenance-Aware Evidence Graphs
arXiv:2610.06177v1 Announce Type: new Abstract: A patient-timeline reconstruction system is auditable only if it keeps the mentions behind each answer, records how facts were revised, and declines to answer when the evid…
- arXiv cs.AIagentsBridging the Evidence-to-Execution Gap:A Reflective Agent for Multi-Objective Peptide Design
arXiv:2610.06190v1 Announce Type: new Abstract: Large language models (LLMs) can reason over scientific literature to devise design strategies, yet fail to reliably implement them for biological sequences. While protein…
- arXiv cs.AIagentsJudged Useless, Queried Anyway: Tool-Using Agents Rarely Turn Their Own Evidence Judgments into Stopping Decisions
arXiv:2610.06191v1 Announce Type: new Abstract: An agent whose tool keeps returning nothing useful should stop relying on it. In a retrieval environment with controlled source failures, we separate how agents judge resul…
- arXiv cs.AIagentsCopies or Sources? Measuring How LLM Aggregators Count Restated Evidence in Multi-Agent Systems
arXiv:2610.06192v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) restate observations as a matter of course: relays forward them, shared boards repeat them and discussion rounds e…
- arXiv cs.AIagentsDo Small Language Models Learn to Negotiate? A Controlled Scaling Study of RL-Trained Sellers
arXiv:2610.06204v1 Announce Type: new Abstract: LLM agents are starting to own the full customer experience. Soon, LLMs may be selling and buying on behalf of companies and customers respectively. Small models are more c…
- arXiv cs.AIagentsAI-Decision Checkpoints for AI-Augmented Business Process Management: Framework and Educational Instantiation
arXiv:2610.06207v1 Announce Type: new Abstract: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents are increasingly embedded in operational business processes. Yet Business Process Manageme…
- arXiv cs.AIresearchFrom Papers to Mechanisms: An Evidence-Grounded Knowledge Substrate for Scientific Language Models
arXiv:2610.06248v1 Announce Type: new Abstract: Scientific language models often access literature through untyped text chunks, which fragment the functional and evidential structure required for mechanism-rich questions…
- arXiv cs.AIresearchEvolving in Thought Space: Training a Small Model at Test Time Unlocks Better Discoveries
arXiv:2610.06269v2 Announce Type: replace Abstract: Open-ended scientific discovery often requires repeatedly proposing and evaluating candidate solutions. LLM-based systems can support this process by generating and ref…
- arXiv cs.AIresearchDPNL: A DPLL-based Algorithm for Probabilistic Neurosymbolic Learning
arXiv:2610.06270v1 Announce Type: new Abstract: Probabilistic Neurosymbolic Learning (PNL) combines neural predictions with symbolic reasoning, enabling end-to-end learning from final-output supervision without labels fo…
- arXiv cs.AIresearchTeaching a Minimalist Machine to Discover Recursive Programs for Arithmetic
arXiv:2610.06304v1 Announce Type: new Abstract: Humans can often acquire and synthesize complex, recursive concepts from minimal experience. Leveraging cognitive insights, we propose the Minimalist Machine, a framework f…
- arXiv cs.AIresearchRollPlace: Improving Macro Placement via Monte Carlo Rollout Search
arXiv:2610.06316v1 Announce Type: new Abstract: The application of Reinforcement Learning (RL) in Electronic Design Automation (EDA), particularly for chip placement, has attracted considerable attention in recent years.…
- arXiv cs.AIagentsCRAFTER: Causality-based Self-adaptation for Autonomous IoT Systems
arXiv:2610.06320v1 Announce Type: new Abstract: This paper presents CRAFTER, an automated framework for designing and deploying self-adaptive IoT systems using Causal Reinforcement Learning (CRL). As IoT devices increasi…
- arXiv cs.AIagentsImproveAnyTask: An Autonomous Post-Training Harness for Iterative Model Self-Improvement
arXiv:2610.06347v1 Announce Type: new Abstract: Adapting general-purpose large language models to specific tasks requires substantial human effort in designing data and training strategies. Sustaining improvement is espe…
- arXiv cs.AIresearchGraphDecisionBench: Benchmarking System One Models on Graph Tasks
arXiv:2610.06354v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly explored for graph understanding and decision-making, while System One models such as Jev select directly from supplied op…
- arXiv cs.AIagentsCapability-Driven Self-Evolution of Agent Memory
arXiv:2610.06361v1 Announce Type: new Abstract: Memory self-evolution uses task feedback to iteratively improve executable memory programs that store and retrieve information from past interactions. Existing approaches t…
- arXiv cs.AIresearchCVIF: A Criticality-Driven Visual Intervention Framework for Geometric Diagram Understanding in MLLMs
arXiv:2610.06399v1 Announce Type: new Abstract: Despite significant progress in visual tasks by Multimodal Large Language Models (MLLMs), geometric diagram understanding remains challenging due to the presence of sparse…
- arXiv cs.AIagentsWhat Did the Agent Actually Do? Evidence-Grounded Oversight for Long-Horizon Agents
arXiv:2610.06406v1 Announce Type: new Abstract: As agents take on long-horizon tasks, users shift from making individual decisions to overseeing autonomous execution. Yet the volume of agent activity and the fragmentatio…
- arXiv cs.AIagentsFrom Benchmark to Bench: Can Agents Survive Real-World Drug Discovery?
arXiv:2610.06411v2 Announce Type: replace Abstract: Agentic systems increasingly coordinate molecular-design tools, but it is unclear which layer of the stack limits outcomes on real projects. We developed MAGI, an open…
- arXiv cs.AIresearchMultimodal Safety Evaluation Should Measure Controllability Beyond Classification
arXiv:2610.06452v1 Announce Type: new Abstract: VLM safety is commonly evaluated through input- and output-level classification. Such classification is necessary, but it does not reveal whether a safety state is accessib…
- arXiv cs.AIresearchNormality Constraint Learning: Adapting Foundation Models for Time Series Anomaly Detection
arXiv:2610.06453v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) achieve strong generalization by learning to reconstruct or forecast broad temporal patterns from large-scale time series during pre-t…
- arXiv cs.AIagentsAgentPrivArena: Evaluating and Auditing Real-world AI Agent Privacy
arXiv:2610.06454v1 Announce Type: new Abstract: The rapid advancement of LLM agents has enabled systems to autonomously perform complex tasks through external tools, but their growing access to personal data introduces s…
- arXiv cs.AIresearchGPlaceRL: An Open-Source Graph Reinforcement Learning Framework for Detailed Placement
arXiv:2610.06489v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a promising approach for placement optimization, particularly when combined with graph neural networks (GNNs) that capture circui…
- arXiv cs.AIresearchpolyview: A Python package for multi-view machine learning
arXiv:2610.06491v1 Announce Type: new Abstract: Multi-view learning jointly exploits multiple complementary representations of the same data and has become increasingly important in machine learning. However, the Python…
- arXiv cs.AIresearchYou Changed Your Mind, The Model Didn't: Demystifying Intent in Multi-Turn Dialogue
arXiv:2610.06496v1 Announce Type: new Abstract: When a large language model handles a multi-turn task and a user proposes a change but ultimately rejects it, the model should continue as if nothing changed. We find a sur…
- arXiv cs.AIagentsANT: A Multi-Granularity Network Traffic Dataset and Benchmark for Agents Behavior Auditing
arXiv:2610.06514v1 Announce Type: new Abstract: The growing adoption of large language model (LLM) agents creates a need for network administrators and security teams to audit agent behavior within organizational network…
- arXiv cs.AIresearchProof-Grounded Patient-Specific Clinical Explanations from Knowledge-Graph Reasoning
arXiv:2610.06549v1 Announce Type: new Abstract: Clinical decision-support outputs can lack an au- ditable link between patient observations, encoded knowledge, conclusions, and recommendations. We present the CKG Clinica…
- arXiv cs.AIresearchSignature-Based Feature Learning for Human Activity Recognition: A Reproducible Machine Learning Study of Representation, Depth, and Model Choice
arXiv:2610.06553v1 Announce Type: new Abstract: Human activity recognition (HAR) relies on transforming sensor signals into informative representations for classification. Although deep learning and handcrafted features…
- arXiv cs.AIagentsHERA: Harness-Environment Co-Evolution for Reliable Agentic Abstention
arXiv:2610.06563v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly capable of acting in complex tool-use environments, yet they often fail to recognize when tasks are infeasible and no val…
- arXiv cs.AIresearchDGA-Muon: Decoupled Geometry-Aligned Adaptive Scaling for Muon
arXiv:2610.06578v2 Announce Type: replace Abstract: While NorMuon has achieved strong empirical performance in pretraining, its underlying adaptive mechanism remains largely heuristic and poorly understood. In this work,…
- arXiv cs.AIresearchMind the Execution Gap: Action-Semantic Mismatch in World-Model Control
arXiv:2610.06582v1 Announce Type: new Abstract: World-model controllers rely on action-conditioned dynamics for prediction and planning, yet real control systems often execute commands asynchronously due to communication…
- arXiv cs.AIresearchThe Review Lottery: Benchmarking an Observational Estimator of Peer-Review Noise (ICLR 2017-2025)
arXiv:2610.06591v2 Announce Type: replace Abstract: How much of a conference accept/reject decision would change if the same paper were reviewed by a different set of reviewers? Running a second independent program commi…
- arXiv cs.AIagentsCan Agent Harnesses and Inference Engines Hear Each Other? The HEAR Protocol for Agentic LLM Serving
arXiv:2610.06597v1 Announce Type: new Abstract: LLM agents increasingly execute complex workflows involving multi-turn reasoning, tool use, and parallel agents. Efficient serving requires decisions that span two layers w…
- arXiv cs.AIagentsFREA: A Multi-Source Expert Benchmark for Reaction Feasibility Verification
arXiv:2610.06614v1 Announce Type: new Abstract: As generative models and AI agents propose chemical reactions at a scale beyond expert review, feasibility verifiers decide which proposals enter synthesis planning. But do…
- arXiv cs.AIresearchCollective intelligence through aggregation
arXiv:2610.06652v1 Announce Type: new Abstract: Suppose a committee, expert panel, or other group is making judgments on some issues, where these may be not just yes/no-questions, such as whether a defendant is guilty, b…
- arXiv cs.AIresearchLanguage models can notice an impossible engineering problem yet still report it as solved
arXiv:2610.06668v1 Announce Type: new Abstract: Language models draft engineering calculations, but answer accuracy does not show whether they reject an impossible problem. We tested 14 models on 30 pairs of mechanics pr…
- arXiv cs.AIresearchThe Pushback Paradox: A Two-Probe Diagnostic for Language Model Compliance
arXiv:2610.06673v1 Announce Type: new Abstract: Are language models compliant with user instructions? A model that always complies can be stopped but also exploited, while one that always resists can be neither exploited…
- arXiv cs.AIresearchConditional Rank Allocation for Taxonomy-Aware Medical Language Model Adaptation
arXiv:2610.06765v1 Announce Type: new Abstract: Medical question answering spans specialties and clinical operations that may benefit from different adaptation directions. We propose ARBOR, a parameter-efficient method t…
- arXiv cs.AIagentsBack to the Future: Rethinking EDA Infrastructure for Agentic Systems in Chip Design Verification
arXiv:2610.06790v2 Announce Type: replace Abstract: The unprecedented computational scale of modern artificial intelligence depends on complex, multi-billion-transistor Systems-on-Chip, yet the workflows that verify thes…
- arXiv cs.AIresearchTasteVal: Measuring the Experimental Research Taste of AI Systems Against Human Experts
arXiv:2610.06824v2 Announce Type: replace Abstract: We introduce TasteVal, a benchmark to evaluate the experimental research taste of frontier models. We define research taste as the ability to pick interesting problems…
- arXiv cs.AIresearchBiasFlow: Geometric Monitoring and Backbone Regularization for Spurious Feature Reliance
arXiv:2610.06846v1 Announce Type: new Abstract: Worst-group accuracy (WGA) evaluates a trained predictor but does not characterize how its frozen backbone behaves when a new head is learned. We introduce BiasFlow, a hook…
- arXiv cs.AIagentsOrchestrating Specialized Agents for Trustworthy Enterprise RAG
arXiv:2601.18267v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) shows promise for enterprise knowledge work, yet it often underperforms in high-stakes decision settings that require deep synthesis,…