AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsDoes Scaling Toward AGI Depend on What System-1 Lets System-2 Execute?
arXiv:2610.39497v1 Announce Type: new Abstract: Progress toward artificial general intelligence (AGI) has largely relied on scaling a resource-intensive executive, System-2, through larger models, more data and compute,…
- arXiv cs.AIresearchIntegrated Feature Selection for classification and Representation Learning with Group-Lasso Siamese Networks
arXiv:2610.39499v1 Announce Type: new Abstract: The Least Absolute Shrinkage and Selection Operator (Lasso) has been widely employed for feature selection in linear models and has also been extended to multi-layer percep…
- arXiv cs.AIresearchWhat Breaks When Facts Become Stories? The Distortions Source-Agreement Metrics Miss When Models Retell Real Events
arXiv:2610.39500v2 Announce Type: replace Abstract: Language models are now widely used to turn recorded facts into media for public consumption, yet evaluation of such output still assumes agreement with the source as i…
- arXiv cs.AIagentsCompile Away Uncertainty: Self-Evolving Agent Skills via Programmatic Compilation
arXiv:2610.39508v1 Announce Type: new Abstract: Self-evolving agent skills enable AI agents to accumulate and refine reusable procedural knowledge from interaction experience without updating model parameters. However, s…
- arXiv cs.AIresearchDEG: Diffusion-Enhanced GFlowNet for Solving Vehicle Routing Problems
arXiv:2610.39512v1 Announce Type: new Abstract: Traditional neural solvers for solving vehicle routing problems (VRPs) often suffer from limited solution diversity, motivating the development of Generative Flow Network (…
- arXiv cs.AIresearchCategory-Anchored Large Language Models for Next POI Recommendation
arXiv:2610.39518v1 Announce Type: new Abstract: Next point-of-interest (POI) recommendation aims to predict a user's next destination from spatio-temporal check-in data, and serves as the foundation for many location-bas…
- arXiv cs.AIresearchNon-Zero Radius: The Missing Component of Neural Networks
arXiv:2610.39559v1 Announce Type: new Abstract: Inspired by the analogy between the all-or-none activation of biological neurons and the true-false of logic circuits, McCulloch and Pitts proposed a mathematical model of…
- arXiv cs.AIagentsFrom Intent to Improvement: Agentic Dataset Search for Better Model Training
arXiv:2610.39608v1 Announce Type: new Abstract: Finding training data in million-scale machine learning repositories is a Web search problem where text relevance is not enough. A query couples a semantic training goal wi…
- arXiv cs.AIresearchEmergence of the transformer architecture as the score of entropic laws of random measures
arXiv:2610.39614v1 Announce Type: new Abstract: We show that the transformer architecture emerges as the score of last-token laws in a natural statistical model of language, where sentences are empirical measures of toke…
- arXiv cs.AIagentsLetting AI Formulate the Research Question: Autonomous Research Agents
arXiv:2610.39620v1 Announce Type: new Abstract: Systems such as The AI Scientist have shown that AI agents can carry out and write up research, but in those demonstrations humans chose the research area and selected the…
- arXiv cs.AIagentsThe Real Cost of Context: Predicting Compute Time and Energy Consumption in LLM Prefill and Decode Phases
arXiv:2610.39621v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into agentic architectures has substantially increased token consumption, raising concerns about their energy footprint. Yet…
- arXiv cs.AIagentsMoLRSI: A Recursive Self-Improving AI agent for Molecular Discovery
arXiv:2610.39714v2 Announce Type: replace Abstract: Molecular discovery requires navigating vast combinatorial search spaces while balancing competing biological objectives. AI agents can automate expert-defined molecula…
- arXiv cs.AIagentsBank-World: A Benchmark for Evaluating Agents on Banking Workflows
arXiv:2610.39733v1 Announce Type: new Abstract: Bank-World is a benchmark of 50 banking tasks across two simulated institutions. Completing banking work requires more than producing the right calculation: agents must rec…
- arXiv cs.AIresearchFrom the Transformer to a Formal Semantics of Coordinated Transformations
arXiv:2610.39735v1 Announce Type: new Abstract: We develop a formal semantics for a general class of coordinated systems of parameterized transformations, taking the Transformer as a paradigmatic starting point but abstr…
- arXiv cs.AIresearchPAPERBENCHX: Can AI Reproduce Science Across Disciplines?
arXiv:2610.39744v1 Announce Type: new Abstract: Before AI can be trusted to discover new science, it should be able to reproduce what science already knows. Reproduction provides a rigorous checkpoint for an AI scientist…
- arXiv cs.AIagentsFinding Is Not Returning, Returning Is Not Reconstructing: A Multi-Dimensional Evaluation of Agent Social Re-entry
arXiv:2610.39781v1 Announce Type: new Abstract: As Large Language Model (LLM) agents increasingly participate in persistent social environments, understanding their long-term social interaction capabilities becomes incre…
- arXiv cs.AIagentsLong-Term Agent Memory through Complementary Curation and Consolidation
arXiv:2610.39790v1 Announce Type: new Abstract: Long-horizon dialogue agents require effective memory systems to recall facts, events, and relationships from interaction histories. In this work, we propose a hybrid-memor…
- arXiv cs.AIresearchThe Role of Self-Concept In Language Models
arXiv:2610.39795v1 Announce Type: new Abstract: When a language model says "I," does it refer to its parameter weights, its currently running process, its stable preferences, its model lineage, or the goals it pursues? D…
- arXiv cs.AIresearchRevisiting Over-refusal in Safety-aligned Large Language Models: A Representation and Optimization Perspective
arXiv:2610.39802v1 Announce Type: new Abstract: Over-refusal is a critical side effect of safety alignment in large language models (LLMs), causing harmless but superficially risky queries to be mistakenly rejected. Desp…
- arXiv cs.AIagentsEvoTeam: Multi-Agent Collaboration via Evolving Teams
arXiv:2610.39813v2 Announce Type: replace Abstract: LLM-based multi-agent systems (MAS) rely on collaboration among specialized agents to solve complex tasks. Existing methods improve MAS by refining the prompts, skills,…
- arXiv cs.AIresearchAegisFlow: Training-Free Non-Myopic Path-Safe Guided Flow Matching
arXiv:2610.39825v1 Announce Type: new Abstract: Pretrained generative models, such as diffusion and flow matching models, have demonstrated exceptional capabilities in synthesizing high-quality data. However, steering th…
- arXiv cs.AIagentsKARMA: Training-Free Knowledge-Atomic Harness Evolution for Industrial Advertising Agents
arXiv:2610.39884v1 Announce Type: new Abstract: Industrial advertising agents must continually adapt their decision knowledge to changing product offerings, traffic patterns, and operating policies. We present KARMA (Kno…
- arXiv cs.AIresearchEfficient Learning of Mechanism Designs and Compositionality
arXiv:2610.40005v1 Announce Type: new Abstract: Learning mechanism behaviour requires a representation of how connected parts jointly constrain motion. We study whether exposing reusable constraint subassemblies improves…
- arXiv cs.AIagentsHuman--AI Interactions as First-Class Data: A Formal Interaction Model and Runtime for Explainable AI Collaboration
arXiv:2610.40006v1 Announce Type: new Abstract: AI assistants are increasingly embedded in computational notebooks, scientific workflows, software engineering tools, and learning systems, yet human-AI interactions are of…
- arXiv cs.AIresearchCheap Retrieval and Observation Credit Assignment from One Quantity: The Value of Information
arXiv:2610.40030v1 Announce Type: new Abstract: Memory in reinforcement learning raises two problems. Attention finds the relevant item by scoring the whole store, which is costly for robots under latency and energy limi…
- arXiv cs.AIagentsHybrid AI Patterns: Thirteen Ways to Couple Language Models with Rules, and How to Choose Among Them
arXiv:2610.40036v1 Announce Type: new Abstract: Language models handle text well, and rule engines give conclusions with proofs. Systems that combine the two are usually described by example, and the same coupling turns…
- arXiv cs.AIagentsAgentic process evidence
arXiv:2610.40071v1 Announce Type: new Abstract: The way software gets built is changing dramatically. AI agents now create pull requests, select dependencies, refactor codebases, interpret test failures, and execute infr…
- arXiv cs.AIresearchReward-Adaptive Co-Evolution of Policy and Rubric
arXiv:2610.40096v1 Announce Type: new Abstract: Rubric-based rewards provide fine-grained, interpretable supervision for open-ended reinforcement learning, where holistic scalar rewards struggle to capture multidimension…
- arXiv cs.AIagentsDynaRev: Benchmarking Web Agents under Dynamic Goal Revision
arXiv:2610.40133v1 Announce Type: new Abstract: Web agents are typically evaluated with goals fully specified before execution and fixed thereafter, whereas real users often revise their requirements during interaction.…
- arXiv cs.AIresearchThe generative paradox: the Anti-Prompt paradigm for human capability
arXiv:2610.40151v1 Announce Type: new Abstract: Generative AI in education is usually judged by the output of human-AI teams. That focus overlooks a second outcome: what people can still understand, challenge, repair, an…
- arXiv cs.AIresearchA Negotiation-Aware Hybrid LLM Framework for Intent Interpretation and Service Discovery
arXiv:2610.40161v1 Announce Type: new Abstract: Increasingly, users express their needs as natural-language intents rather than structured requests. These intents may be incomplete, high-level, or internally conflicting.…
- arXiv cs.AIagentsLocating and Closing Information Gaps in Multi-Agent Systems
arXiv:2610.40186v1 Announce Type: new Abstract: Multi-step Web tasks often require several LLM agents to gather and combine evidence. The communication graph of a fixed workflow restricts which agents can read each other…
- arXiv cs.AIresearchBridging Semantics and Structure: A Theoretically Grounded Framework for Link Prediction on TAGs
arXiv:2610.40192v1 Announce Type: new Abstract: Link prediction on text-attributed graphs (TAGs) is a fundamental problem with applications in knowledge discovery, recommendation and beyond. Recent progress has highlight…
- arXiv cs.AIagentsEpiAgent: Epistemic Self-Play for LLM Agents
arXiv:2610.40227v1 Announce Type: new Abstract: Epistemic game theory explains an agent's strategic behavior via the beliefs it holds about others and how these beliefs are updated as the interactions unfold. Modern LLM-…
- arXiv cs.AIagentsEnvOS: Auditing Computer-Use Agents When the World Moves On : Phenomenon-Based Task Construction, Certification, and Evidence-Based Evaluation
arXiv:2610.40246v1 Announce Type: new Abstract: Computer-use agents built on large language models (LLMs) work in software that can change while they act: an appointment moves, a policy is revised, a record is updated. T…
- arXiv cs.AIresearchReaction precedents extend retrosynthetic prediction beyond training coverage
arXiv:2610.40249v1 Announce Type: new Abstract: Reaction precedents guide retrosynthesis, but how far they can compensate for gaps in task-specific training coverage remains unclear. Using 2.71 million reactions, we rest…
- arXiv cs.AIresearchDistributional Reward Calibration and Budget-Neutral Credit Assignment for Multimodal RLVR
arXiv:2610.40250v1 Announce Type: new Abstract: We revisit advantage estimation in Group Relative Policy Optimization (GRPO) and observe that any token-level advantage admits a two-stage factorization: a \emph{sample-lev…
- arXiv cs.AIresearchNeighborhood Elites: Quality-Diversity Search for Uncertainty Quantification in Question Answering
arXiv:2610.40278v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly capable, yet they produce wrong answers indistinguishable from correct ones. In question answering (QA), such an error propaga…
- arXiv cs.AIresearchMultistep and Multivariate Time Series Explainability with GradientSHAP: A Wind Power Case Study
arXiv:2610.40330v1 Announce Type: new Abstract: As the effects of climate change become increasingly apparent, the demand for renewable energy sources such as wind power continues to grow. However, renewables' variable a…
- arXiv cs.AIresearchBeyond Selected Breakthroughs: Evaluating Language Models on Randomly Sampled Mathematical Conjectures
arXiv:2610.40382v1 Announce Type: new Abstract: The last year has seen a shift in AI-assisted mathematics, with frontier language models producing proofs of and counterexamples to long-standing open conjectures. However,…
- arXiv cs.AIresearchRetrieving from Your Own Mistakes: On-Policy Training of Embedding Models for Multi-Hop Retrieval-Augmented Generation
arXiv:2610.40409v1 Announce Type: new Abstract: Complex questions in retrieval-augmented generation require evidence spread over several documents, and an answer is reliable only when the retriever finds all of it. Chain…
- arXiv cs.AIagentsPrefix Executability: Evaluating Tool-Using Agents Beyond Final Success
arXiv:2610.40444v1 Announce Type: new Abstract: Tool-use benchmarks often score agents by final task success, but terminal outcomes can obscure whether the intermediate tool-call trajectory was executable. We propose pre…
- arXiv cs.AIresearchTraining language models in simulation for psychiatric intake
arXiv:2610.40476v1 Announce Type: new Abstract: In psychiatric practice, the clinical intake interview remains a primary diagnostic instrument, requiring the clinician to establish rapport while disentangling complex, ov…
- arXiv cs.AIagentsFIRME: Registry-Anchored Memory Graphs for Evolving, Heterogeneous Investor Knowledge
arXiv:2610.40482v1 Announce Type: new Abstract: Financial AI workflows that reuse investor knowledge need persistent memory that integrates observations across sources and periods without losing identity or provenance. I…
- arXiv cs.AIagentsAgentic University: Collaborative Agents for Personalized Learning
arXiv:2610.40492v1 Announce Type: new Abstract: Large language models support personalized tutoring, content generation, and adaptive learning paths. However, capability development requires these resources and interacti…
- arXiv cs.AIresearchAlgebraic World Model: From Exploration to Proofs
arXiv:2610.40503v2 Announce Type: replace Abstract: AI has made remarkable progress in mathematics, solving challenging problems with machine-checkable proofs in Lean, yet typically relying on predefined mathematical def…
- arXiv cs.AIresearchEfficient Scalable Oversight via Rewinding
arXiv:2610.40535v1 Announce Type: new Abstract: Scalable oversight asks how a weak verifier can check the outputs of computations performed by more powerful AI systems. One proposed approach uses relativizing interactive…
- arXiv cs.AIresearchOn the Fundamental Limits of Prefill-Based Decoding Length Prediction
arXiv:2610.40541v1 Announce Type: new Abstract: Predicting how many tokens a large language model (LLM) will decode, using only prefill-phase hidden states, is a key primitive for inference scheduling. We show that curre…
- arXiv cs.AIagentsRetrieval as Traversal: Value-Indexed Memory for Stateful Long-Context Agents
arXiv:2610.40545v1 Announce Type: new Abstract: Long-context models repeatedly solve closely related retrieval problems. Attention or global retrieval can retain large stores, but each forward pass again searches for wha…
- arXiv cs.AIresearchRamanujan Challenge Results: AI-Assisted Evaluation Pipeline for Multi-Format Proofs
arXiv:2610.40551v1 Announce Type: new Abstract: As AI's mathematical capabilities rapidly improve, meaningful benchmarks are shifting from university-level problems and math olympiads to research-level mathematics. The R…