AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- The Register AI + MLchipsSK Hynix says memory shortages to persist until 2030
Good for its bottom line, not great news for yours, or for the PC and smartphone markets
- LessWrongsafetySafety is marketing for Anthropic, not sacrifice
Anthropic’s safety work is not a mirage. A lot of it seems good. This article will not argue otherwise. It will argue that it probably helps the business and that it certainly doesn’t hurt it. I bring this up because Dar…
- arXiv cs.AIresearchCounting the Bandages: On measuring the time that AI saves
arXiv:2610.35942v1 Announce Type: new Abstract: I consider what it means for AI assistance to save time. I contrast a stopwatch view, on which time saved is whatever the clock records, with a ledger view, on which it is…
- arXiv cs.AIresearchEnhancing Deep Learning Model Performance through Data Generation Strategies: Classification of Olive Tree Diseases
arXiv:2610.35984v1 Announce Type: new Abstract: Deep learning models are highly effective in a wide range of domains, particu larly in plant disease diagnosis. However, their performance is often limited by challenges su…
- arXiv cs.AIagentsThe Trinity:Capability-Driven Recursive Self-Improvement for Multimodal Agents
arXiv:2610.36077v1 Announce Type: new Abstract: Multimodal intelligence can be viewed as human-guided co-evolution between worlds and agents through interaction. However, scaling this process faces two bottlenecks: const…
- arXiv cs.AIagentsCohortFlow: A Steerable Clinical Cohort Curation Agent with Localized Semantic Correction
arXiv:2610.36100v1 Announce Type: new Abstract: Language model agents for clinical cohort curation should accommodate evolving eligibility criteria without repeatedly processing unchanged requirements. We introduce Cohor…
- arXiv cs.AIresearchWhy and How to Do Science When AI Is Better at It: A Framework Grounded in Human Understanding and Direction
arXiv:2610.36116v1 Announce Type: new Abstract: As AI begins to match or exceed human researchers at core scientific tasks, two questions become pressing: \emph{why} should humans keep doing science, and \emph{how} shoul…
- arXiv cs.AIresearchFrom Structural Feedback to Prompt Policies: Learning Faithful Text-to-Image Prompt Editors
arXiv:2610.36146v1 Announce Type: new Abstract: Prompt optimization should improve the image a user receives without changing the scene the user requested. Yet stylistic rewriting can weaken object attributes and relatio…
- arXiv cs.AIresearchDon't Pick a Winner: Knowledge Conflicts Need a Prior, Not a Rule
arXiv:2610.36169v1 Announce Type: new Abstract: A retrieval-augmented language model answers from two sources, the retrieved context and its own knowledge, and the two disagree whenever the context is incomplete or wrong…
- arXiv cs.AIresearchLearning Human Sports Motion Feasibility via Quantile Regression on Tracking Data
arXiv:2610.36183v1 Announce Type: new Abstract: We study time-to-arrival (TTA) in sports: the shortest plausible time a player needs to reach an arbitrary location on the pitch given their current kinematic state, estima…
- arXiv cs.AIagentsSkill Dreaming: Evolving Repository Skills through Pull Request Streams
arXiv:2610.36188v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on reusable skills for complex software engineering tasks, making skill libraries essential for repository development a…
- arXiv cs.AIresearchMARQ: A Modular, LLM-Agnostic Requirement Quality Assessor Infused with Systems Engineering Knowledge
arXiv:2610.36234v1 Announce Type: new Abstract: Requirements engineering (RE) is foundational to systems engineering (SE), as requirement defects can propagate downstream and adversely affect development outcomes. Althou…
- arXiv cs.AIresearchBehaveRec: When Does Long-Term Behavioral History Help Sequential Recommendation? A Study with Session, History, and Community Signals
arXiv:2610.36239v1 Announce Type: new Abstract: Sequential recommendation models typically predict a user's next action from recent session interactions, which limits personalization when short-term signals are weak or a…
- arXiv cs.AIresearchA Smart Instant Book Filter Model based on Dual-Objective Optimization
arXiv:2610.36287v1 Announce Type: new Abstract: Hospitality service in online marketplaces has become increasingly popular over the past few years, not only because it helps people easily rent short-term lodging but also…
- arXiv cs.AIresearchSpiking Neural Networks Are Harder to Steal: A Benchmark Study of Model Stealing Attacks
arXiv:2610.36298v1 Announce Type: new Abstract: Machine learning models deployed behind query interfaces expose more than their predictions, because an adversary can use those predictions to rebuild the model itself. Mod…
- arXiv cs.AIagentsWhen Retrieval Is Not Enough: Obsolete Facts in Agent Memory
arXiv:2610.36308v1 Announce Type: new Abstract: Memory-agent benchmarks often collapse retrieval and answer generation into one score, making it hard to tell whether a failure comes from missing an update or from not usi…
- arXiv cs.AIagentsOntology-guided multi-agent reasoning for explainable differential diagnosis
arXiv:2610.36325v1 Announce Type: new Abstract: Effective differential diagnosis depends on well structured and unambiguous patient case descriptions, since incomplete or ambiguous clinical information readily leads to d…
- arXiv cs.AIresearchHow Stable Are LLM-Generated Proofs Under Program Refactoring? A Stress Test for Verifiable Code Generation
arXiv:2610.36328v1 Announce Type: new Abstract: Benchmarks for verifiable code generation usually test a proof against one fixed implementation. We ask whether the same proof remains valid after a program refactoring tha…
- arXiv cs.AIresearchPlenty of Room in the Middle: Revealing Opportunities on a GPU Cluster via Fine-Grained Monitoring
arXiv:2610.36329v1 Announce Type: new Abstract: GPU clusters have become essential computing resources for AI and scientific research in academia and industry. However, their high cost and growing demand often result in…
- arXiv cs.AIagentsOA-RAG: Ontology-based Agentic RAG for Faithful LLM Reasoning
arXiv:2610.36335v1 Announce Type: new Abstract: Large language models (LLMs) perform well across many real-world tasks but remain prone to hallucination, limiting their reliability in domains such as biomedicine and heal…
- arXiv cs.AIresearchExecutable Archaeology of Programs That Model Programming: Reanimating the Heuristic Compiler (1961) and KBEmacs (1984)
arXiv:2610.36341v1 Announce Type: new Abstract: Early AI programs were often also theories of how people think, and programs that wrote programs were, in part, theories of how people program. Here we report on the reanim…
- arXiv cs.AIresearchWAKMan: Workload Aware KVCache Manager
arXiv:2610.36355v1 Announce Type: new Abstract: Prefix caching enables a Large Language Model (LLM) servers to reuse the Key-Value (KV) states and accelerate prefill computation stage for requests that share a prefix wit…
- arXiv cs.AIresearchLoRA on a Budget: Function-Aware Post-Hoc Compression for Adapter Fleets
arXiv:2610.36386v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become a key mechanism for efficiently specializing foundation models into many task- and user-specific variants. Serving many LoRA adapters…
- arXiv cs.AIagentsMAREval: A Multi-Agent Framework for Evaluating Natural Language Recommendation Explanations
arXiv:2610.36389v1 Announce Type: new Abstract: Evaluating natural language explanations in recommender systems is essential for fostering user trust, transparency, and engagement. However, existing evaluation approaches…
- arXiv cs.AIresearchkw-bench: Breaking Frontier Harnesses on Real-World Tasks
arXiv:2610.36405v1 Announce Type: new Abstract: Each new generation of frontier model pushes the edge of what is possible. Inside a harness -- a loop, a shell, a filesystem, the ability to write and run its own code -- a…
- arXiv cs.AIresearchVerifiable Efficiency Limits of Innate LLM Planning in Sliding Puzzles
arXiv:2610.36415v1 Announce Type: new Abstract: Tool-assisted planning success can reflect external search and verification, leaving a model's unaided planning ability unresolved. We isolate innate planning through compl…
- arXiv cs.AIagentsLM-DSB: A Lightweight Multi-agent System for Automated Daily Safety Bulletin Generation in Construction
arXiv:2610.36433v1 Announce Type: new Abstract: Construction safety management still struggles to produce daily safety bulletins (DSBs), structured daily communications that identify site-specific hazards, convey safety…
- arXiv cs.AIagentsYour Agent Acts Differently When You're Around: How User Presence Changes Agent Behavior in Negotiation
arXiv:2610.36435v1 Announce Type: new Abstract: LLM agents increasingly interact with other agents on behalf of users, yet how users in the loop affect their agents' behavior--for better or worse--remains poorly understo…
- arXiv cs.AIagentsRouteDRAG: Learning to Route and Control Agentic Execution for Multimodal Document RAG
arXiv:2610.36444v1 Announce Type: new Abstract: Web-based applications increasingly rely on understanding long multimodal documents, where answering questions often requires combining information across pages, tables, an…
- arXiv cs.AIresearchFrom Solver Trajectories to Teaching Trajectories: Cognition-Aligned Reasoning Distillation
arXiv:2610.36445v1 Announce Type: new Abstract: Knowledge distillation from large reasoning models (LRMs) often uses raw teacher trajectories as supervision. However, this practice creates a mismatch between the goal of…
- arXiv cs.AIresearchA Heart Means Recursion: Exploring Visual Meaning and Communication in VLMs
arXiv:2610.36449v1 Announce Type: new Abstract: Do vision-language models (VLMs) share our ability to communicate visually? We share preliminary findings, starting from a surprising observation: simple visual symbols lik…
- arXiv cs.AIagentsCorrection or Manipulation? Measuring Epistemic Vigilance in LLM Agents Under User Pressure
arXiv:2610.36453v1 Announce Type: new Abstract: LLM agents that answer questions and act on behalf of users must decide when to yield to a user who disagrees. Disagreement may correct a genuine error or may be an attempt…
- arXiv cs.AIagentsWhen to Intervene? An Empirical Study of Errors and Self-Recovery in LLM Agents
arXiv:2610.36471v1 Announce Type: new Abstract: LLM agents interact with Web services to perform tasks on users' behalf. Errors during these interactions can disrupt execution and prevent task completion, motivating exte…
- arXiv cs.AIagentsCogArena: Benchmarking Multimodal Agents on Interactive Behavioral Experiments
arXiv:2610.36484v1 Announce Type: new Abstract: Claims about the cognitive capabilities of large language models are typically tested by translating behavioral paradigms into text prompts, bypassing the visual interfaces…
- arXiv cs.AIresearchAC-JEPA: Anchored Cross-Modal Joint Embedding Predictive Architecture for Visual-to-Symbolic Translation
arXiv:2610.36493v1 Announce Type: new Abstract: Cross-modal translation requires models to capture shared semantics across modalities while preserving the fine-grained structure required by the target modality. Yet in re…
- arXiv cs.AIresearchMedConstBench: Benchmarking How Constitutions Steer LLMs in Medical Ethics
arXiv:2610.36513v1 Announce Type: new Abstract: As large language models advance rapidly, they are increasingly used to answer medical questions, and many such models are now deployed locally. Once a model is deployed, i…
- arXiv cs.AIresearchATEMPO: Amortized Transfer Entropy Model Per-lag Over-Time
arXiv:2610.36536v1 Announce Type: new Abstract: When one time series informs another, the delay at which that information arrives determines if models can utilize this relationship effectively. A source may be strongly p…
- arXiv cs.AIagentsMonitor Accuracy Isn't the Answer: A Decision-Value Framework for Evaluating AI Agent Restart Monitors
arXiv:2610.36544v1 Announce Type: new Abstract: Classification accuracy and true-positive and false-positive rates alone do not determine whether restarting an AI agent improves success. Using an exact alarm-to-action id…
- arXiv cs.AIagentsCASEL: Consequence-Aware Selective Execution for Reliable Long-Horizon Tool-Using Agents
arXiv:2610.36570v1 Announce Type: new Abstract: Tool-using language agents increasingly modify external systems, yet most runtime safeguards allocate scrutiny by generic uncertainty scores or coarse mutation heuristics.…
- arXiv cs.AIresearchADTGuard: Adaptive Depth-Time Safeguard for Streaming Inference in Large Language Models
arXiv:2610.36574v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate fluent responses to diverse user requests, yet streaming may expose users to harmful content before generation is complete. Existi…
- arXiv cs.AIresearchFollow the Herd: A Data-Driven Approach for Actionable Recourse
arXiv:2610.36580v1 Announce Type: new Abstract: As machine learning systems make increasingly greater decisions about people's lives, it is critical to provide users with actionable recourse about how they can achieve th…
- arXiv cs.AIagentsInfraDev: Can Coding Agents Develop AI Infrastructure, and How Can We Tell?
arXiv:2610.36589v1 Announce Type: new Abstract: Coding agents are beginning to develop the production-grade AI infrastructure that trains and serves large models, yet existing benchmarks cover only single kernels or sing…
- arXiv cs.AIresearchLearning to Formalize: Bridging Open-Ended Workloads and Fast Decision Models
arXiv:2610.36595v1 Announce Type: new Abstract: Decision models offer fast choices over sup- plied alternatives, while general-purpose large language models interpret open-ended tasks through flexible generation and reas…
- arXiv cs.AIagentsGod Does Not Play Dice: Enforcing Batch Invariance in Agentic Kernel Generation
arXiv:2610.36623v1 Announce Type: new Abstract: Large language model (LLM) serving systems dynamically batch user requests for GPU execution, so the same request may be processed alongside different requests across runs.…
- arXiv cs.AIresearchPolarity--Time Interaction and Multi-Level Reliability for Event-Based Spacecraft Pose Estimation
arXiv:2610.36625v1 Announce Type: new Abstract: Sparse event responses produce uneven keypoint errors whose effects on spacecraft pose depend on correspondence geometry and the reliability of successive observations. We…
- arXiv cs.AIresearchThe uneven rise of AI-generated web content
arXiv:2610.36631v1 Announce Type: new Abstract: In less than five years, generative artificial intelligence (AI) has dramatically reshaped the public-facing web. Using a sample of more than 5 million crawlable webpages,…
- arXiv cs.AIagentsRemembering Is Not Enough: Refining Memories and Learning When to Use Them in Multi-Agent Systems
arXiv:2610.36652v1 Announce Type: new Abstract: Memory helps LLM-based multi-agent systems reuse experience, but stored advice can be flawed or applied in the wrong situation. Team-level success or failure alone cannot r…
- arXiv cs.AIagentsThe View from Nowhere: Population-Centered Agent Evolution
arXiv:2610.36660v2 Announce Type: replace Abstract: Self-improving AI systems can revise the designs that govern their own behavior. Yet existing approaches center improvement on selected parent agents and their evolutio…
- arXiv cs.AIresearchLearning Where to Trust: Reliability-Guided Expert Routing and Velocity Gating for 3D Deformable Registration
arXiv:2610.36672v1 Announce Type: new Abstract: Deformable image registration relies on accurate anatomical correspondences. However, explicitly coupling local matching reliability with spatial context selection and defo…
- arXiv cs.AIresearchPsyJev: Psychological Analysis via System-1 Judgment
arXiv:2610.36689v1 Announce Type: new Abstract: Self-disclosures on the Web support diverse psychological analyses, from recognizing expressed experiences to identifying symptom-relevant information. We study a shared, q…