AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAdvancing Clinical Genomic Analysis with a Skill-Centred Agent
arXiv:2610.40556v1 Announce Type: new Abstract: Clinical genomic analysis requires experts to integrate evolving guidelines, databases, and computational evidence. As sequencing has become increasingly accessible, this c…
- arXiv cs.AIresearchFARMS: A Verifiable Foundation for Automated Computational Science
arXiv:2610.40560v1 Announce Type: new Abstract: Automated computational science could accelerate discovery by selecting, adapting and developing numerical methods. This prospect requires mathematical knowledge that AI sy…
- arXiv cs.AIresearchComparing Human Role-Players and LLM-Simulated Clients in Online Counselling Training: An Analysis of Counselling Patterns
arXiv:2610.40563v1 Announce Type: new Abstract: This study investigates the capabilities of Large Language Models to simulate counselling clients in educational role-plays in comparison to human role-players. Initially,…
- arXiv cs.AIagentsVeriCUA: Verification as Agentic Exploration for Computer-Using Agents
arXiv:2610.40578v1 Announce Type: new Abstract: Building and scaling computer-using agents (CUAs) across desktop, mobile, and web environments requires reliable task-completion verification for data curation, evaluation,…
- arXiv cs.AIagentsPre-Crime for Agents, at the Last Second: Probing When a Recruited Agent Gives In
arXiv:2610.40588v1 Announce Type: new Abstract: When AI agents share channels and credentials, one agent can press another to break its operator's rule, a first step towards collusion. Output filters check only what an a…
- arXiv cs.AIagentsCollaborative AI agents for autonomous experimental research with solid-state quantum spins
arXiv:2610.40589v1 Announce Type: new Abstract: An autonomous research laboratory could conduct an entire study, from formulating questions to preparing manuscripts. Artificial intelligence (AI) offers one route towards…
- arXiv cs.AIresearchLLM-Integrated Bayesian State Space Models for Multimodal Time-Series Forecasting
arXiv:2510.20952v1 Announce Type: cross Abstract: Forecasting in the real world requires integrating structured time-series data with unstructured textual information, but existing methods are architecturally limited by…
- arXiv cs.AIresearchArtifact Distillation: Training-Free Transfer from Frontier to Small Language Models
arXiv:2610.37680v1 Announce Type: cross Abstract: Closing the gap between frontier and smaller language models is usually approached by distillation: fine-tuning the small model (student) on a frontier model's (teacher)…
- arXiv cs.AIresearchSupervised Fine-Tuning for Reasoning Large Language Models: A Survey
arXiv:2610.37681v1 Announce Type: cross Abstract: Large reasoning models have recently demonstrated remarkable capabilities in solving complex tasks, where supervised fine-tuning (SFT) on long chain-of-thought data serve…
- arXiv cs.AIresearchRank-Aware Differentially Private Release of Listwise Preferences for LLM Alignment
arXiv:2610.37682v1 Announce Type: cross Abstract: Listwise preference feedback offers richer supervision for large language model (LLMs) alignment than pairwise comparisons, but a full ranking also reveals more sensitive…
- arXiv cs.AIresearchPrompt-agnostic Language Models
arXiv:2610.37683v1 Announce Type: cross Abstract: Despite their strong performance, large language models remain highly sensitive to prompt formulation. This issue is typically addressed at inference-time through manual…
- arXiv cs.AIresearchAn Introduction to Large Language Models for Scientists and Professionals
arXiv:2610.37684v1 Announce Type: cross Abstract: Large Language Models (LLMs) have rapidly become important tools for science, education, medicine, and professional work. Despite their apparent simplicity from the user'…
- arXiv cs.AIresearchFrom Geometry to Behavior: How Instruction Exposure Unlocks Latent Rhetorical Directions in LLMs
arXiv:2610.37685v1 Announce Type: cross Abstract: Language models do not merely memorize facts; they absorb rhetorical strategies from pretraining data, including the human tendency to reason by analogy. We ask: is this…
- arXiv cs.AIresearchWhere Planning Changes the Outcome of Orbital Games
arXiv:2610.37686v1 Announce Type: cross Abstract: This paper introduces OrbitalGym, a simulation environment for studying when planning algorithms or system design determine the outcome of adversarial orbital encounters.…
- arXiv cs.AIresearchOne Confidence Threshold, Unequal Coverage: Language Gaps in Typed Decision Interfaces and How Translating Inputs Reduces Them
arXiv:2610.37688v1 Announce Type: cross Abstract: Deployed classifiers often act on a prediction only when its confidence clears a threshold and pass the rest to a person. We ask whether one threshold serves all language…
- arXiv cs.AIresearchGenAI as an 'Invisible Hand' in Opinion Dynamics: Evidence from a Group-Level Simulation Study
arXiv:2610.37689v1 Announce Type: cross Abstract: Recent arguments suggest that genAI can act as an invisible hand that gradually shapes social structures, such as collective beliefs and norms. The argument is that if mi…
- arXiv cs.AIagentsCassette-Editor: A Video Editing Agent That Edits the Way You Do
arXiv:2610.37690v1 Announce Type: cross Abstract: Language agents increasingly work by calling tools on a persistent artifact, such as a code repository, and the result of each call shapes their next step. Video editing…
- arXiv cs.AIresearchBouba Beats Kiki, and Other Regularities in the Subjective Preferences of LLMs
arXiv:2610.37692v1 Announce Type: cross Abstract: Users engage with large language models on tasks that are purely objective ("When was Netflix founded?"), purely subjective ("What should I name my child?") or anywhere i…
- arXiv cs.AIagentsNetwork Topology Does Not Matter: The Breakdown of Classical Consensus in LLM Populations
arXiv:2610.37699v1 Announce Type: cross Abstract: As multi-agent language model networks become widely deployed, predicting their collective behavior is a critical challenge. Classical distributed consensus theory relies…
- arXiv cs.AIagentsThe Coordination Tax and the Heterogeneity Dividend: Break-Even Conditions for Multi-Agent LLM Pipelines
arXiv:2610.37700v1 Announce Type: cross Abstract: Multi-agent LLM pipelines built on interoperability protocols such as the Open Floor Protocol (OFP) or A2A are usually justified on capability grounds, with their runtime…
- arXiv cs.AIresearchDuQUAD: A Dual-View Framework with Quality-Aware Evidence Pruning for Multi-Document Question Answering
arXiv:2610.37701v1 Announce Type: cross Abstract: Large language models with retrieval-augmented generation systematically underutilize evidence in the middle of multi-document contexts, a phenomenon known as Lost in the…
- arXiv cs.AIresearchSearch-Guided Reasoning Trace Curation for Verilog Generation
arXiv:2610.37706v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have improved Verilog generation. However, most training pipelines distill natural-language reasoning traces whose interme…
- arXiv cs.AIresearchFVH-Bench: Evaluating Image Generator Safety Beyond Overtly Harmful Imagery
arXiv:2610.37722v1 Announce Type: cross Abstract: Modern image generators can produce complex visual artifacts, including diagrams, interfaces, and records that combine text, graphics, and layout to convey detailed infor…
- arXiv cs.AIresearchPredicate Neuron: Differentiable Quantization of Predicate Relations in Gradient-based Learning
arXiv:2610.37727v1 Announce Type: cross Abstract: In machine learning, symbolic reasoning approaches often rely on static architectures that hinder integration into deep neural networks and gradient-based optimization. T…
- arXiv cs.AIresearchBeyond Similarity Search: Knowledge Graph Metadata Enrichment for Enterprise Retrieval-Augmented Generation
arXiv:2610.37728v1 Announce Type: cross Abstract: A key challenge of RAG systems is retrieving information from enterprise documents created by multiple teams over time, where it is not possible to enrich the information…
- arXiv cs.AIresearchSelective Transfer Learning for Groundwater Level Anomaly Forecasting: Accuracy-Risk Trade-offs
arXiv:2610.37733v1 Announce Type: cross Abstract: This work studies context-aware selective transfer learning for multi-well groundwater anomaly forecasting in the Netherlands. Source-domain pretraining can raise average…
- arXiv cs.AIagentsWhen Skills Tell Agents Not to Ask: A Large-Scale Study of Oversight Directives in Agent Skills
arXiv:2610.37734v1 Announce Type: cross Abstract: Agent skills, reusable instruction packages centred on a SKILL.md file, extend AI agents on demand, and a single line in a widely copied skill reaches every agent that lo…
- arXiv cs.AIagentsPoisoned Skills: Propagating Jailbreaks Through Agent Markdown Files
arXiv:2610.37738v1 Announce Type: cross Abstract: Modern agent frameworks allow users to provide Markdown files containing system prompts, tool descriptions, and skill definitions (e.g., SKILL.md), which are incorporated…
- arXiv cs.AIresearchEUReCA: End-to-End Unified CBCT Reconstruction Across Clinical Acquisitions
arXiv:2610.37740v1 Announce Type: cross Abstract: Cone-beam computed tomography (CBCT) is widely used for image-guided radiotherapy, but reducing the number of projections to lower dose and scan time makes reconstruction…
- arXiv cs.AIagentsLocating Sycophancy Across Training Stages in Open Language Models
arXiv:2610.37788v1 Announce Type: cross Abstract: Language model assistants sometimes change a correct answer when the user suggests a wrong one. The behavior, called sycophancy, is usually attributed to preference-based…
- arXiv cs.AIresearchSpokes, not a Ring: Revisiting the Weekday Manifold in Language Models
arXiv:2610.37796v1 Announce Type: cross Abstract: Recent work has hypothesised that large language models may represent some concepts as multi-dimensional manifolds instead of single directions. Using these manifolds to…
- arXiv cs.AIresearchResponsible Quantum Machine Learning for Medical Imaging: A Fairness Audit Across Sensitive Subgroups
arXiv:2610.37819v1 Announce Type: cross Abstract: Quantum machine learning (QML) is increasingly explored for medical classification, yet its behaviour under subgroup-aware fairness criteria remains understudied. We pres…
- arXiv cs.AIresearchDeFT-RAG: Decomposing Multi-Hop Questions into Self-Contained Sub-Questions with Reusable Answers
arXiv:2610.37826v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) lets a large language model (LLM) answer questions by retrieving relevant passages from a large corpus. However, RAG struggle…
- arXiv cs.AIresearchLearning Lotteries with Minimal Stakeholder Violations from Membership Queries
arXiv:2610.37828v1 Announce Type: cross Abstract: An AI developer often has several candidate versions of a system and can deploy a mixture of them, sending each request to a randomly chosen version, as in A/B testing. E…
- arXiv cs.AIresearchWhere the Error Lives: Spectral Representations of Learned Kohn-Sham Hamiltonians
arXiv:2610.37843v1 Announce Type: cross Abstract: Kohn-Sham density functional theory (DFT) is the standard method for computing the electronic structure of molecules and materials, but its self-consistent-field (SCF) it…
- arXiv cs.AIresearchEcho: Scaling Visual Reinforcement Learning with Off-policy Experience
arXiv:2610.37865v1 Announce Type: cross Abstract: Scaling visual reinforcement learning (RL) with GPU-accelerated simulation is computationally expensive due to rendering and visual-policy inference costs. Consequently,…
- arXiv cs.AIresearchPairCLIP-SWA: Similarity-Guided Balancing and Stochastic Weight Averaging for Generalized Deepfake Image Detection with OpenCLIP
arXiv:2610.37874v1 Announce Type: cross Abstract: Deepfake detectors are almost always deployed as the single checkpoint that scored best on a validation split, yet the reliability of that choice is rarely measured. We m…
- arXiv cs.AIresearchWhen More Planning Hurts: Learned Planners for World Models
arXiv:2610.37891v1 Announce Type: cross Abstract: On PushT, our fixed action updater (1,505 parameters) solves 8 of 16 scenes reserved from our configuration selection. The comparison planners perform as follows: Selecte…
- arXiv cs.AIagentsScan Before You Install: Detecting and Mitigating Local and Composite Vulnerabilities in Skills
arXiv:2610.37901v1 Announce Type: cross Abstract: An agent skill packages natural-language instructions, scripts, and reference files that an LLM-based agent loads for a task. Skills may access the file system, shell, an…
- arXiv cs.AIresearchThink Twice: The Metis-1.6 Technical Report
arXiv:2610.37903v1 Announce Type: cross Abstract: Metis is a bet that better data, better training methods and new architectures can buy what a bigger parameter count cannot, at a fraction of the cost. Metis-1.6 is its l…
- arXiv cs.AIresearchTERRA: Task-Oriented Edge AI for Regional Fire Detection with Identity-Free Reporting
arXiv:2610.37909v1 Announce Type: cross Abstract: Distributed fire-monitoring systems may involve many sensing devices reporting over a shared uplink, even though the operational objective is often to identify regions ex…
- arXiv cs.AIresearchWhat Actually Matters? A Paired Evaluation of Inference Settings for $\pi_{0.5}$ on BEHAVIOR-1K
arXiv:2610.37917v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models offer a promising paradigm for general-purpose household robotics. However, inference and data-collection strategies that have been de…
- arXiv cs.AIresearchNLP-based Message Prioritisation for Opportunistic Routing: A Case Study of Nepal Earthquake Emergency Communication
arXiv:2610.37933v1 Announce Type: cross Abstract: This dissertation investigates whether Natural Language Processing (NLP) based semantic message prioritisation can improve the treatment of urgent disaster messages in op…
- arXiv cs.AIresearchSAG-Sep: Sparse Augmented Graphs and Onion-Guided Search for Rounded Capacity Cut Separation
arXiv:2610.37952v1 Announce Type: cross Abstract: Rounded capacity cuts (RCCs) are among the most effective cuts for capacitated vehicle-routing relaxations, but exact separation is computationally prohibitive at scale.…
- arXiv cs.AIresearchStatistical Detection of Positional Bias in LLM-Based Recommender Systems: Methodologies and Empirical Evidence
arXiv:2610.37962v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used as recommendation generators in conversational recommender systems (RS) via retrieval-augmented generation (RAG). This…
- arXiv cs.AIresearchSelf-Supervised Latent Action-Conditioned World Modeling for Time Series
arXiv:2610.37963v1 Announce Type: cross Abstract: Time-series data play an important role in various tasks, such as weather forecasting, web traffic analysis, and speech recognition. Recently, pioneering studies have inc…
- arXiv cs.AIresearchMerge and Branch: Efficient Tree-Structured Supervised Fine-Tuning of LLMs for Recommendation
arXiv:2610.37973v1 Announce Type: cross Abstract: LLM-based generative recommendation reads long, text-rich interaction histories but generates only short semantic identifiers (SIDs). This asymmetry makes supervised fine…
- arXiv cs.AIresearchTowards Generalizing Pretrained All-Atom Representations to Unified Binder Design
arXiv:2610.37994v1 Announce Type: cross Abstract: PairFormer-based all-atom models demonstrate strong capabilities in biomolecular binder design. However, existing methods often use all-atom representations for modality-…
- arXiv cs.AIresearchAre Seismic Foundation Models More Than Glorified Feature Extractors?
arXiv:2610.38003v1 Announce Type: cross Abstract: Earthquake sequences are stochastic on two separated timescales: the seismic waves of any individual earthquake propagate over seconds to minutes, while the earthquakes t…
- arXiv cs.AIresearch"It Would Make a Geordie Feel at Home": Regional Accent Perceptions and Speech Accommodation in Voice AI
arXiv:2610.38005v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) systems often perform less accurately for speakers of regional dialects, but less is known about how users respond to these limitations…