AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAutomating Feature Flag Cleanup at Scale with Multi-Agent LLM Systems: An Industrial Experience at DoorDash
arXiv:2610.31351v1 Announce Type: cross Abstract: Feature flags are runtime configuration mechanisms used for gradual feature rollouts, experimentation, and kill switches. Once a feature is fully rolled out, the flag and…
- arXiv cs.AIresearchAI Risk Ontologies for the EU AI Act Compliance: AIRO, VAIR, and their Integration with DPV
arXiv:2610.31380v1 Announce Type: cross Abstract: As the use of AI, and consequently its harms, becomes more prevalent, the global discourse around AI has become increasingly risk-aware. With new risks emerging more freq…
- arXiv cs.AIresearchAuditing the Hand-Written Inputs of Learned Access Control
arXiv:2610.31388v1 Announce Type: cross Abstract: Learned access control is typically deployed behind two hand-built artefacts: a hard-deny set enforced by a small trusted shield, and a region map that decides which requ…
- arXiv cs.AIresearchHERD: Harness-Evolving Recursive Distillation for Continual Learning
arXiv:2610.31401v1 Announce Type: cross Abstract: Continual learning requires a model to keep acquiring new skills and knowledge without compromising its existing capabilities. Parametric methods suffer from catastrophic…
- arXiv cs.AIagentsAgentPhishing: A Benchmark of LLM Email Agents Under Adaptive Attack
arXiv:2610.31404v1 Announce Type: cross Abstract: Computer-use agents increasingly handle private information and act on users' behalf across desktop and web applications, including email. Phishing therefore poses privac…
- arXiv cs.AIresearchSame Entity, Different Script: Diagnosing Cross-Script Entity Matching Failures in Language Models
arXiv:2610.31407v1 Announce Type: cross Abstract: Multilingual language models can give different identity judgments when the same people's names are written in different scripts. We study this effect using 601 audited i…
- arXiv cs.AIresearchMajor Revision, Minor Accountability: LLMs as Reviewers of Published Articles in Top-Tier Journals
arXiv:2610.31414v1 Announce Type: cross Abstract: With the growth of scientific output, the peer review system is approaching a breaking point: reviewers are increasingly hard to secure, and turnaround times lengthen acc…
- arXiv cs.AIresearchPost-Hoc Feature Selection Layer for Neural Networks Interpretability
arXiv:2610.31420v1 Announce Type: cross Abstract: The interpretability of complex neural networks remains a critical challenge, especially for models already deployed in high-stakes domains. To address this, we adapted t…
- arXiv cs.AIresearchHow Depth Growth and Looping Shape In-Context Learning in Language Models
arXiv:2610.31421v1 Announce Type: cross Abstract: Looped and depth-grown language models reuse computations across depth and have attracted interest for their reasoning capabilities. Building on prior suggestive evidence…
- arXiv cs.AIresearchFocusVLA: Future-Intent Guided Dynamic View Routing for Vision-Language-Action Models
arXiv:2610.31423v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have become an important paradigm for robotic manipulation by unifying visual perception, language understanding, and action generatio…
- arXiv cs.AIresearchPredictable performance is suboptimal, and what it means for model routing
arXiv:2610.31428v1 Announce Type: cross Abstract: Large language models (LLMs) differ in capabilities and costs, motivating routing methods that adaptively choose a model for each query. These methods rely on performance…
- arXiv cs.AIresearchMoG-VLM: Efficient Video Anomaly Detection through Motion-Guided Vision-Language Models
arXiv:2610.31478v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have shown strong potential for video anomaly detection, but dense frame-level inference makes them impractical for real-time deployment. Ex…
- arXiv cs.AIagentsTraining Small Language Models for Transferable Tool Selection
arXiv:2610.31483v1 Announce Type: cross Abstract: As LLM agents operate over corpora of more than ten thousand tools, selecting the right tool for a complex multi-step user instruction becomes a central bottleneck. Tool…
- arXiv cs.AIresearchSABLE: Scalable Affine Bayesian Latent-space Exploration
arXiv:2610.31495v2 Announce Type: replace-cross Abstract: Complex objects such as engineering designs and proteins are often difficult to optimise because their design spaces exhibit high-dimensional structure and object…
- arXiv cs.AIresearchThe Geometry of Metaphor: Probing and Steering Metaphor Representations in Large Language Models
arXiv:2610.31520v1 Announce Type: cross Abstract: Metaphor is a crucial aspect of human cognition. As such, we would like to understand how it is represented in large language models (LLMs) and how it might be controlled…
- arXiv cs.AIresearchWhen to Follow the Teacher: Advantage-Based On-Policy Distillation
arXiv:2610.31563v1 Announce Type: cross Abstract: Online Policy Distillation (OPD) often outperforms offline methods such as Supervised Fine-Tuning (SFT) by training on trajectories sampled directly from the student. How…
- arXiv cs.AIresearchSocial-HUMINT: An LLM-Augmented Unified Framework for Measuring Social Media Exposure
arXiv:2610.31573v1 Announce Type: cross Abstract: In the post-API landscape, social-media profiling has become inexpensive and automated: Large Language Models (LLMs) can extract structured information from unstructured…
- arXiv cs.AIresearchWould an LLM Match into a Residency? Uncertainty, Reasoning and Image Use of Open Language Models on the Spanish MIR Examination
arXiv:2610.31586v1 Announce Type: cross Abstract: Accuracy on medical examinations is common evidence offered for the clinical use of language models, yet a health system that intends to run an open model on its own hard…
- arXiv cs.AIresearchVERA: A Responsible AI Dashboard for Assessing LLM Deployments in Light of the EU AI Act
arXiv:2610.31588v1 Announce Type: cross Abstract: Institutions that deploy large language models in regulated settings often need technical evidence of responsible AI practices before approving a deployment. COMPL-AI pro…
- arXiv cs.AIresearchHow Ground Truth Shapes Retrieval Scores: Evidence-Aware Evaluation of a Retrieval-Augmented Generation System for Breast Lesions
arXiv:2610.31606v2 Announce Type: replace-cross Abstract: Purpose: To describe an evidence-aware retrieval evaluation protocol for a clinical retrieval-augmented generation (RAG) system over breast lesion management lite…
- arXiv cs.AIagentsQuestioning Instrumental Convergence in RLVR: Checkpoint Evidence from OLMo-3
arXiv:2610.31624v1 Announce Type: cross Abstract: Instrumental convergence is often invoked as a general reason to expect capable agents to acquire or express power-seeking subgoals: self-preservation, resource acquisiti…
- arXiv cs.AIresearchCausal Chain of Thought: Mitigating Attention Leakage via Context Isolation
arXiv:2610.31639v1 Announce Type: cross Abstract: Chain-of-thought (CoT) prompting elicits step-by-step rationales that appear to explain model predictions, but there is no guarantee these steps causally drive the final…
- arXiv cs.AIresearchLow-Bit N-Gram Embeddings for Language Models
arXiv:2610.31646v1 Announce Type: cross Abstract: Many recent open-weight language models use n-gram embedding tables to improve performance. These tables store learned representations of short token sequences, such as p…
- arXiv cs.AIagentsMETTA: Memory-Enhanced Test-Time Adaptation for Meta-Reinforcement Learning
arXiv:2610.31656v1 Announce Type: cross Abstract: Meta-reinforcement learning aims to train agents that adapt quickly to unseen tasks from limited interaction, but this requires representing task evidence over long inter…
- arXiv cs.AIresearchCost-Aware Abstention for LLM-Based IT Ticket Classification
arXiv:2610.31657v1 Announce Type: cross Abstract: Wrong automatic routing of an IT support ticket can cost more than human triage. We evaluate cost-aware abstention as an offline, cost-conditional readiness assessment: s…
- arXiv cs.AIresearchAnchoring Distributed Agency: Institutional Metaphors for Designing Large-Scale AI and AI Techniques for Running Institutions
arXiv:1803.03407v3 Announce Type: replace Abstract: Artificial Intelligence (AI) started out with the ambition to reproduce the human mind, but as soon as the sheer scale of that ambition became apparent, it retreated in…
- arXiv cs.AIresearchRisk-Aware Alignment Must Incorporate Reward Uncertainty
arXiv:2410.23726v2 Announce Type: replace Abstract: We consider the problem of policy optimization with noisy rewards, where the policy is constrained to be in the neighborhood of a reference policy.We study the risk of…
- arXiv cs.AIresearchGroup Contrastive Policy Optimization: Learning Beyond the Self-Exploration Limit with Golden Answers
arXiv:2510.07790v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a powerful paradigm for improving the reasoning abilities of large language models, yet group-based met…
- arXiv cs.AIresearchHow to Teach Large Multimodal Models New Skills
arXiv:2510.08564v3 Announce Type: replace Abstract: How can we teach large multimodal models (LMMs) new skills without erasing prior abilities? We study sequential fine-tuning on five target skills while monitoring gener…
- arXiv cs.AIresearchMENTOR: A Metacognition-Driven Self-Evolution Framework for Uncovering and Mitigating Implicit Domain Risks in LLMs
arXiv:2511.07107v5 Announce Type: replace Abstract: Ensuring the safety of Large Language Models (LLMs) is critical for real-world deployment. However, current safety measures often fail to address implicit, domain-speci…
- arXiv cs.AIresearchGFlowPO: Generative Flow Network as a Language Model Prompt Optimizer
arXiv:2602.03358v2 Announce Type: replace Abstract: Finding effective prompts for language models (LMs) is critical yet notoriously difficult: the prompt space is combinatorially large, rewards are sparse due to expensiv…
- arXiv cs.AIresearchSleepMaMi: A Universal Sleep Foundation Model for Integrating Macro- and Micro-structures
arXiv:2602.07628v3 Announce Type: replace Abstract: While the shift toward unified foundation models has revolutionized many deep learning domains, sleep medicine remains largely restricted to task-specific models that f…
- arXiv cs.AIresearchSci-CoE: Co-evolving Scientific Reasoning LLMs via Geometric Consensus with Sparse Supervision
arXiv:2602.12164v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated exceptional reasoning capabilities, and co-evolving paradigms have shown promising results in domains with verifiable rew…
- arXiv cs.AIagentsCLEAR: Context Augmentation from Contrastive Learning of Experience via Agentic Reflection
arXiv:2604.07487v3 Announce Type: replace Abstract: Large language model agents rely on effective model context to obtain task-relevant information for decision-making. Many existing context engineering approaches primar…
- arXiv cs.AIagentsSkillFlow: Flow-Driven Recursive Skill Evolution for Agentic Orchestration
arXiv:2605.14089v2 Announce Type: replace Abstract: In recent years, a variety of powerful LLM-based agentic systems have been applied to automate complex tasks through task orchestration. However, existing orchestration…
- arXiv cs.AIresearchProjecting Latent RL Actions: Towards Generalizable and Scalable Graph Combinatorial Optimization
arXiv:2605.19721v2 Announce Type: replace Abstract: Graph combinatorial optimization (GCO) has attracted growing interest, as many NP-hard problems naturally admit graph formulations, yet their combinatorial explosion re…
- arXiv cs.AIresearchXetrieval: Explaining Dense Retrieval through Feature Elicitation
arXiv:2605.29507v2 Announce Type: replace Abstract: Dense retrieval enables effective semantic matching, yet the semantic factors underlying its relevance scores remain opaque. Sparse autoencoders (SAEs) support feature-…
- arXiv cs.AIagentsMLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery
arXiv:2606.06473v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE), where sustained se…
- arXiv cs.AIagentsManimAgent: Self-Evolving Multimodal Agents for Visual Education
arXiv:2606.30296v3 Announce Type: replace Abstract: Multi-round reflection lets agents built on large language models recover from failures within a single task, but each task remains an isolated episode: lessons learned…
- arXiv cs.AIagentsHow Far Can Root Cause Analysis Go on Real-World Telemetry Data?
arXiv:2607.13548v2 Announce Type: replace Abstract: Root cause analysis (RCA) of microservice failures requires reasoning over telemetry far larger than a model's context, so a language agent reasons over extracted evide…
- arXiv cs.AIresearchDGA$_2$D: Directed Graph-Guided Automated Algorithm Design with Large Language Models
arXiv:2608.00700v2 Announce Type: replace Abstract: The rapid development of Large Language Models (LLMs) has opened new avenues for Automated Heuristic Design (AHD) for solving NP-hard combinatorial optimization problem…
- arXiv cs.AIagentsEvaluating Rational Contracting in Natural Language
arXiv:2608.10475v2 Announce Type: replace Abstract: The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard-coded protocols…
- arXiv cs.AIagentsFrom Faulty Memories to Corrected Actions: Dependency-Guided Rollback Repair for Memory-Augmented Agents
arXiv:2608.10502v2 Announce Type: replace Abstract: Persistent memory lets language model agents reuse information across sessions, but it also makes errors durable: a poisoned, stale, or misattributed record can alter r…
- arXiv cs.AIresearchWhen Self-Consistency Backfires: Majority Vote Hurts the Majority of Hard Science Problems for Small LLMs
arXiv:2608.11403v3 Announce Type: replace Abstract: Majority-vote self-consistency (SC) lowers per-problem accuracy on most GPQA Diamond problems for small instruction-tuned models: on 56.6% of problems for Qwen2.5-7B an…
- arXiv cs.AIresearchD2R2: Discrete Diffusion with Regulation Reinforcement for Single-Cell Perturbation Prediction
arXiv:2608.15288v2 Announce Type: replace Abstract: Predicting single-cell transcriptomic responses to genetic perturbations is central to functional genomics and virtual-cell modeling. Existing approaches, however, typi…
- arXiv cs.AIagentsTRCA: Transition-wise Rubric Credit Assignment for Long-horizon LLM Agents
arXiv:2608.16156v2 Announce Type: replace Abstract: Long-horizon large language model (LLM) agents are typically optimized with sparse terminal outcomes, making fine-grained credit assignment across multi-step interactio…
- arXiv cs.AIresearchWhen Prediction Error Is Not Enough: Evaluating Nuisance-Function Prediction for Causal Estimation
arXiv:2609.00071v3 Announce Type: replace Abstract: Prediction error is widely used to evaluate nuisance-function estimators in causal inference, but its relationship with the performance of the resulting causal estimato…
- arXiv cs.AIresearchLEBGen: An LLM-Enhanced Bayesian Network Framework for Few-Shot Travel Survey Data Generation
arXiv:2609.08288v2 Announce Type: replace Abstract: Travel survey data are essential for transportation planning and travel behavior analysis, yet collecting large-scale representative samples is costly and time-consumin…
- arXiv cs.AIresearchEvolutionary Deep Nets for Non-Intrusive Load Monitoring
arXiv:2303.03538v2 Announce Type: replace-cross Abstract: Compact appliance classifiers can support local electricity-load monitoring where memory and computation are constrained. We evaluate adaptive sparse evolutionary…
- arXiv cs.AIresearchHearing the shape of an arena with spectral swarm robotics
arXiv:2403.17147v2 Announce Type: replace-cross Abstract: Swarm robotics relies on robots with minimal sensing and computation that achieve self-organization at the level of the collective to address a variety of tasks.…