AI news archive.
19,854 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchThe Commit-Abstain Circuit: Why Language Models Hallucinate Instead of Abstaining
arXiv:2609.32964v2 Announce Type: replace Abstract: Language models (LMs) often hallucinate by committing to confident answers rather than abstaining, even when they do not have enough information to answer reliably. A l…
- arXiv cs.AIagentsRelic: From Multi-Agent Collaboration to Persistent Organizational Capability
arXiv:2609.32965v2 Announce Type: replace Abstract: Multiple agents may often conflict in an organization: for example, one coding agent changes an interface in a repository, but another continues to develop on the old v…
- arXiv cs.AIagentsCertified Long-Horizon Code Agent Evolution via Validation-Gated Skill Optimization
arXiv:2609.32990v1 Announce Type: new Abstract: Long horizon agent self-evolution without model weight updates is essential for enabling deployed agents to accumulate reusable skills and improve over time. Prior self-evo…
- arXiv cs.AIagentsX-Tree: Tokenizing Reusable Experience for Efficient Agent Generalization
arXiv:2609.32993v1 Announce Type: new Abstract: Multi-step agents are trained on flat action streams: SFT and RLVR weight every token uniformly and ignore the sub-procedures that recur across tasks, the hierarchy that le…
- arXiv cs.AIresearchModel-Aware Data Selection from In-and-Out Information Interplay
arXiv:2609.33010v1 Announce Type: new Abstract: LLMs are effective representations that assimilate vast amounts of knowledge during pretraining, but post-training is necessary for models to reliably access this knowledge…
- arXiv cs.AIagentsWhen Pair Count Is Not the Sample Size: What All-Pairs Agent Comparisons Estimate
arXiv:2609.33012v1 Announce Type: new Abstract: When an agent benchmark compares every pair of leaderboard entries, the number of comparisons can look much larger than the independent evidence behind them: A versus B and…
- arXiv cs.AIagentsThe Epistemics of Agent Memory: Measuring, and Governing, the Consolidation Decision in Long-Horizon LLM Agents
arXiv:2609.33013v1 Announce Type: new Abstract: Long-horizon LLM agents must convert accumulated experience into durable memory, deciding what to keep, compress, abstract into reusable skills and rules, or forget. We rep…
- arXiv cs.AIagentsTrust and Task Completion in the World of Consumer AI Agents
arXiv:2609.33017v1 Announce Type: new Abstract: Action agents do things for people. They send email, spend money, and call businesses while the user is busy with something else, so a mistake can turn into an action befor…
- arXiv cs.AIagentsSRE-Marathon: A Continuous, Change-Driven Benchmark for Autonomous Site Reliability Agents
arXiv:2609.33023v1 Announce Type: new Abstract: Benchmarks for site reliability engineering (SRE) agents are typically episodic: one fault is injected, the agent receives an incident task, and its response is scored. Pro…
- arXiv cs.AIagentsAgent Safety From Within: Detecting Harmful Trajectories from LLM Internal States
arXiv:2609.33039v1 Announce Type: new Abstract: Language model agents can now perform sophisticated sequences of actions via tools and harnesses, which has increased the scope of the damage they can cause. Guard models,…
- arXiv cs.AIresearchBudgetVerify: Budget-Tiered Verification for Financial QA
arXiv:2609.33052v1 Announce Type: new Abstract: Financial question answering often requires precise numerical extraction, unit handling, and arithmetic over tables and text, but applying expensive verification uniformly…
- arXiv cs.AIresearchLarge Language Models Substantially Compress Well-Being Dispersion but Largely Preserve Its Socioeconomic Structure
arXiv:2609.33055v2 Announce Type: replace Abstract: Research using large language models (LLMs) to generate synthetic populations shows that model outputs compress human variation. We ask whether this compression also di…
- arXiv cs.AIresearchLLM sequential decision making under uncertainty in biochemical domains
arXiv:2609.33061v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to drive scientific discovery. Understanding how LLMs make decisions from new data and memory of the literature is vital…
- arXiv cs.AIresearchQureRadEmbed: Structuring Radiological Similarity through Attribute and Reasoning Supervision
arXiv:2609.33075v1 Announce Type: new Abstract: Radiological similarity depends on disease relationships and on fine details such as laterality, lobe, severity, size, and certainty. Broad biomedical similarity can overlo…
- arXiv cs.AIresearchStructure-Mapping-Guided Self-Explanation for Learning Mathematical Procedures
arXiv:2609.33079v1 Announce Type: new Abstract: Worked examples are a powerful form of instruction, but learners must infer how the demonstrated steps were produced. A naive simulation of this self-explanation process ca…
- arXiv cs.AIresearchThe Model Knows Another Way: Strategy Switching for Effective RLVR Exploration
arXiv:2609.33085v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is often limited by insufficient exploration: difficult problems can yield uniformly incorrect rollout groups and ther…
- arXiv cs.AIresearchModular Discovery of General Game-Playing Algorithms with Large Language Models
arXiv:2609.33115v1 Announce Type: new Abstract: General Game Playing across arbitrary games from rules alone remains challenging due to differing algorithmic requirements across game classes and strict decision-time cons…
- arXiv cs.AIagentsCompositional Safety Failures in Harness Evolution: Identification and Runtime Monitoring
arXiv:2609.33123v3 Announce Type: replace Abstract: Self-evolving agent harnesses continually update persistent components such as memory, prompts, skills, and tools. We call this process harness evolution. However, such…
- arXiv cs.AIresearchCeiling of a Task: When Can a Transformer Succeed Without Its Chain of Thought?
arXiv:2609.33134v1 Announce Type: new Abstract: Reasoning models generate long chains of thought before they answer, yet it is debated whether the content of these chains does real computational work or is largely decora…
- arXiv cs.AIagentsOn Device Agentic Operation Caches -- Classifier-Centric NL-to-Action Generation
arXiv:2609.33141v1 Announce Type: new Abstract: Agentic AI is increasingly being embedded in software applications to provide natural language interfaces to features and functionality. In most cases these agents are powe…
- arXiv cs.AIagentsLiteEvo: Automated, Cost-Efficient Harness Evolution for Generalization to Unseen Tasks
arXiv:2609.33146v1 Announce Type: new Abstract: An LLM agent is defined by two things: the weights inside its model and the harness of components assembled around it. Harnesses are still handcrafted, and HarnessX, which…
- arXiv cs.AIresearchNot Too Hard, Not Too Easy: Learning from Intermediate States for LLM Structured Reasoning
arXiv:2609.33149v2 Announce Type: replace Abstract: A common principle of effective learning is to practice material that is neither already mastered nor too difficult to permit progress. We ask how to apply this princip…
- arXiv cs.AIresearchSeOPD: Self-Evolving LLMs via Online Policy Distillation from Self-Generated Chain-of-Thought
arXiv:2609.33181v2 Announce Type: replace Abstract: Recent advances in online policy self-distillation (OPSD) have demonstrated that large language models (LLMs) can improve their capabilities by leveraging external priv…
- arXiv cs.AIresearchUnlocking Latent Personalization in LLMs
arXiv:2609.33182v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly expected to adapt to individual users, yet effective personalization remains challenging when only limited user-specific sampl…
- arXiv cs.AIresearchAre Benchmarks Reliable? Toward Structural Diagnosis via Item-Level Capability Boundaries
arXiv:2609.33196v2 Announce Type: replace Abstract: Evaluating large language models (LLMs) relies heavily on benchmark scores, yet aggregate metrics can obscure whether individual items serve their intended measurement…
- arXiv cs.AIagentsWorldAgent: Verification-Guided Agentic Physical World Construction
arXiv:2609.33208v1 Announce Type: new Abstract: Constructing complex physical worlds from language requires coordinating extensive 3D environments, detailed structures and objects at different spatial scales, and interac…
- arXiv cs.AIagentsCodeSkill: Latent Skill Abstraction for Long-Horizon Code Agents
arXiv:2609.33243v2 Announce Type: replace Abstract: Code agents require long-horizon decision-making over complex interaction trajectories. However, existing reinforcement learning (RL) approaches typically optimize beha…
- arXiv cs.AIagentsActiveMem: Dynamic Latent Memory Trees for Long-Horizon Agents
arXiv:2609.33244v2 Announce Type: replace Abstract: Large Language Model (LLM) agents increasingly rely on external memory to support long-horizon reasoning and decision making. Existing memory systems typically retrieve…
- arXiv cs.AIagentsCORTEX: A Verified Experience Layer for Generalist Agents
arXiv:2609.33260v1 Announce Type: new Abstract: An agent can solve a task today and face the same task under new facts, tools, or governing knowledge tomorrow. Most agent systems can retrieve relevant text or recall prio…
- arXiv cs.AIagentsLSTMem: Hierarchical Long Short-Term Online Memory for Large Language Models
arXiv:2609.33268v2 Announce Type: replace Abstract: Large language models increasingly serve as long-horizon assistants and agents, where they must both accumulate information across interactions and make the relevant pa…
- arXiv cs.AIresearchStructured Sparse Memory for Recurrent Reasoning
arXiv:2609.33270v1 Announce Type: new Abstract: Recurrent models trained from scratch have recently become competitive on ARC-style reasoning tasks, but the usual framing around small recurrent backbones overlooks two im…
- arXiv cs.AIresearchNext Thoughts Are Distributions: Generative Autoregressive Reasoning in the Latent Space
arXiv:2609.33271v1 Announce Type: new Abstract: Reasoning problems often admit multiple valid ways to proceed. Continuous reasoning promises to move computation beyond language tokens into a more compact latent space, bu…
- arXiv cs.AIresearchChronoFlow: Hierarchical Flow Matching for Irregular Time Series Generation
arXiv:2609.33276v1 Announce Type: new Abstract: Recent advances in generative modeling have substantially improved time series generation, yet most existing methods either assume a regular temporal grid or focus on featu…
- arXiv cs.AIresearchMulti-Dimensional Comparative Scale Construction for Efficient Personalized Subjective Judgment in High-Traffic Applications
arXiv:2609.33282v1 Announce Type: new Abstract: Subjective judgments are central to many high-traffic applications, but subjective intensity is difficult to quantify and perceptions vary substantially across individuals.…
- arXiv cs.AIresearchRINI: Seeing the Prior Is Not Enough
arXiv:2609.33284v1 Announce Type: new Abstract: A research proposal can describe an established mechanism correctly while claiming to introduce it. We study whether providing the earlier paper corrects such contribution…
- arXiv cs.AIresearchFeedback Makes Perfect: A Closed-Loop Framework for NL-to-STL Translation
arXiv:2609.33287v1 Announce Type: new Abstract: Signal Temporal Logic (STL) enables rigorous verification and control of cyber-physical systems, but writing correct specifications requires expertise that most requirement…
- arXiv cs.AIagentsLearning to Sell: Reinforcement Learning for Strategic Large Language Model Agents in Multi-Product Markets
arXiv:2609.33289v2 Announce Type: replace Abstract: Autonomous large language model (LLM) agents operating in multi-product markets must make sequential decisions under information asymmetry and resource constraints. We…
- arXiv cs.AIagentsTraceDance: An Automated System for Building Agent Behavior Benchmarks from Real-World Agent Deployment Traces
arXiv:2609.33295v1 Announce Type: new Abstract: An agent can complete a task while exhibiting undesirable behavior during execution. Developers need tests for the specific behaviors encountered in deployment, beyond fixe…
- arXiv cs.AIresearchThe Error You See Is Not the Error You Made: Progression-aware Reasoning Origin for Reasoning Error Localization
arXiv:2609.33297v1 Announce Type: new Abstract: Verifying multi-step LLM reasoning requires more than determining whether a trace is correct: a useful verifier should identify where the reasoning first goes wrong. Howeve…
- arXiv cs.AIresearchPhysAlign: A Benchmark for Evidence-Grounded Role Alignment in Multimodal Physics Reasoning
arXiv:2609.33319v1 Announce Type: new Abstract: A key challenge in physics diagram understanding is correctly associating visual information with the physical entities, relations, and conditions it describes. Even when a…
- arXiv cs.AIagentsAgentic Multi-Turn Reasoning: A Fairness Approach
arXiv:2609.33323v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems capable of solving complex tasks through multi-turn planning, tool use, verification, and memor…
- arXiv cs.AIagentsANTMAN: Adaptive Need Tracking for Multi-Agent Navigation in Large Information Spaces
arXiv:2609.33326v1 Announce Type: new Abstract: Information-seeking agents increasingly operate over information spaces that are too large to process exhaustively. Yet many multi-agent systems organize computation around…
- arXiv cs.AIresearchNaturalness-guided Manifold Flow Matching for Sign Language Production
arXiv:2609.33339v1 Announce Type: new Abstract: Sign Language Production (SLP) aims to generate sign motions from text. Conditional Flow Matching methods have achieved strong performance in SLP by constructing conditiona…
- arXiv cs.AIresearchQuPID: Quantum Parameter-Efficient Input-Dependent Retrieval Adaptation for Medical RAG
arXiv:2609.33351v1 Announce Type: new Abstract: Fidelity-based quantum retrieval ranks candidates by the fidelity between query and archive states. Applying a shared input-independent unitary after fixed state encoding l…
- arXiv cs.AIresearchUnmask the State: When Does State Adaptation Matter for Masked Diffusion Language Models
arXiv:2609.33355v1 Announce Type: new Abstract: Masked diffusion language models (MDMs) admit flexible generation orders, making the unmasking strategy an inference decision. Existing methods vary in how they prioritize…
- arXiv cs.AIagentsLong-Horizon Analog Design Bench: Benchmarking Agents on Hours-Long Analog and Mixed-Signal Circuit Design Tasks
arXiv:2609.33356v1 Announce Type: new Abstract: Coding agents now sustain hours-long, tool-driven loops, yet their ability to carry long-horizon analog and mixed-signal circuits to electrical specification remains unmeas…
- arXiv cs.AIagentsDISCERN: Can AI Agents Work Like Scientists and Guide Discovery?
arXiv:2609.33357v2 Announce Type: replace Abstract: Reliable automated research requires agents to vet data, verify analyses, and generate hypotheses grounded in trustworthy evidence, potentially reducing routine scienti…
- arXiv cs.AIresearchDrafTS: Time-Aware Decomposition with Residual Correction for Time Series Modeling
arXiv:2609.33368v1 Announce Type: new Abstract: Real-world time series contain evolving underlying dynamics with irregular variations that lack stable temporal patterns and are often referred to as noise. Existing method…
- arXiv cs.AIresearchCross-modal Translation via Conditional Latent Denoising for Video Deepfake Detection
arXiv:2609.33394v1 Announce Type: new Abstract: The growing threat of video deepfakes necessitates multimodal detection. Beyond serving as independent indicators of authenticity, audio and visual signals have intrinsic d…
- arXiv cs.AIresearchCoViST: Visual Token Compression via Composable States
arXiv:2609.33397v1 Announce Type: new Abstract: Visual token compression lowers the inference cost of vision--language models by representing images with fewer tokens. However, most existing methods compress visual token…