AI news archive.
19,885 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchExactness at Inference: A Representational Criterion for Out-of-Distribution Generalization
arXiv:2609.24942v1 Announce Type: cross Abstract: A model generalizes outside its training distribution only when it computes a representation structurally equivalent to the generating mechanism, not an approximation fit…
- arXiv cs.AIresearchGenerative Tutorial: Towards Live Contextualized Visual Instructions for Physical Tasks
arXiv:2609.24955v1 Announce Type: cross Abstract: Visual instructions for physical tasks are typically authored in one context and followed in another, requiring users to translate demonstrated tools, materials, and spat…
- arXiv cs.AIagentsJev for Scientific Decisions: Evaluating Semantic Choices and Their Consequences
arXiv:2609.24965v4 Announce Type: replace-cross Abstract: Scientific workflows often require choosing among known relations before a deterministic calculation can proceed. Whether observations share a culture, treatment…
- arXiv cs.AIagentsRare Event Estimation via Iterative Unalignment
arXiv:2609.24969v1 Announce Type: cross Abstract: As agents are deployed with increased autonomy, even extremely rare events along their stochastic output trajectories can occur and prove catastrophic. Safe deployment th…
- arXiv cs.AIagentsDolphinBench: Mapping the Pareto Frontier of Agent Memory
arXiv:2609.24971v2 Announce Type: replace-cross Abstract: Agents today often take real-world actions that depend on long-term memory and context recall over time. However, most current memory benchmarks are built for a c…
- arXiv cs.AIagentsRRSI: Regularized Recursive Self-Improvement of Agent Harnesses
arXiv:2609.24972v3 Announce Type: replace-cross Abstract: An LLM agent's capability is largely magnified by its harness, namely the prompts, control flow, tooling, memory, and context management surrounding the frozen ba…
- arXiv cs.AIresearchDexTacWAM: A Visuo-Tactile World-Action Model for Dexterous Manipulation
arXiv:2609.24976v1 Announce Type: cross Abstract: Dexterous manipulation depends on contact dynamics that are often only partially observable from vision. Recent World-Action Models (WAMs) couple predictive video world m…
- arXiv cs.AIresearchWorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory
arXiv:2609.24984v1 Announce Type: cross Abstract: Video world models enable interactive exploration of dynamic environments, yet struggle to respect prior observations over long horizons and across viewpoints. We present…
- arXiv cs.AIresearchGameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay
arXiv:2609.25001v2 Announce Type: replace-cross Abstract: Modern video games provide a measurable testbed for AI models, combining abilities of visual understanding, instruction decomposition, goal planning, and precise…
- arXiv cs.AIresearchSubgoal Search For Complex Reasoning Tasks
arXiv:2108.11204v4 Announce Type: replace Abstract: Humans excel in solving complex reasoning tasks through a mental process of moving from one idea to a related one. Inspired by this, we propose Subgoal Search (kSubS) m…
- arXiv cs.AIagentsControlling risks of AI in chemical science with agents
arXiv:2312.06632v2 Announce Type: replace Abstract: Artificial intelligence is rapidly advancing scientific discovery, but this progress carries risks of misuse, such as the creation of harmful substances, or circumventi…
- arXiv cs.AIresearchRL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner
arXiv:2410.23912v3 Announce Type: replace Abstract: The reasoning abilities of large language models (LLMs) have improved with chain-of-thought (CoT) prompting, allowing models to solve complex tasks stepwise. However, t…
- arXiv cs.AIresearchFairness at Every Intersection: Uncovering and Mitigating Intersectional Biases in Multimodal Clinical Predictions
arXiv:2412.00606v3 Announce Type: replace Abstract: Biases in automated clinical decision-making using Electronic Healthcare Records (EHR) impose significant disparities in patient care and treatment outcomes. Convention…
- arXiv cs.AIagentsDivide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning
arXiv:2505.13994v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy trade-offs when scaling…
- arXiv cs.AIresearchMemory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models
arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range of real-world tasks…
- arXiv cs.AIagentsPADiff: Predictive and Adaptive Diffusion Policies for Ad Hoc Teamwork
arXiv:2511.07260v3 Announce Type: replace Abstract: Ad hoc teamwork (AHT) requires agents to collaborate with previously unseen teammates, which is crucial for many real-world applications. The core challenge of AHT is t…
- arXiv cs.AIresearchChemVTS-Bench: Evaluating Visual-Textual-Symbolic Reasoning of Multimodal Large Language Models in Chemistry
arXiv:2511.17909v2 Announce Type: replace Abstract: Chemical reasoning inherently integrates visual, textual, and symbolic modalities, yet existing benchmarks rarely capture this complexity, often relying on simple image…
- arXiv cs.AIagentsAgentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation: A Case Study in Decision Support for Rice Cultivation in Japan
arXiv:2512.21066v4 Announce Type: replace Abstract: Explainable artificial intelligence (XAI) reveals how explanatory variables relate to a response variable, yet communicating XAI outputs to laypersons remains difficult…
- arXiv cs.AIresearchCARD: Cluster-level Adaptation with Reward-guided Decoding for Personalized Text Generation
arXiv:2601.06352v3 Announce Type: replace Abstract: Adapting large language models to individual users remains challenging due to the tension between fine-grained personalization and scalable deployment. We present CARD,…
- arXiv cs.AIresearchDo Implicit Personalization and Explicit Styles Conflict? PsPLUG: A Lightweight Plug-in for Balancing Personalization and Style in Customized LLMs
arXiv:2601.06362v3 Announce Type: replace Abstract: Personalized large language models are often expected to follow explicit style instructions, yet we find that such instructions can undermine the user-specific characte…
- arXiv cs.AIagentsA Survey of Agentic Reasoning for Large Language Models: Towards Recursively Self-Improving and Collective Agents
arXiv:2601.12538v2 Announce Type: replace Abstract: Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) demonstrate strong reasoning…
- arXiv cs.AIagentsReplayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents
arXiv:2601.15322v4 Announce Type: replace Abstract: Replaying a financial agent requires specifying the conditions of a rerun, preserving its execution record, and deciding which parts of its behavior to compare. We intr…
- arXiv cs.AIresearchVeRA: Renewing Reasoning Benchmarks with Executable Specifications
arXiv:2602.13217v2 Announce Type: replace Abstract: Reasoning benchmarks need renewal along two axes: freshness and headroom. VeRA makes both executable and auditable by turning each item into a task family: a natural-la…
- arXiv cs.AIresearchWhen can we trust untrusted monitoring? A safety case sketch across collusion strategies
arXiv:2602.20628v2 Announce Type: replace Abstract: AIs are increasingly being deployed with greater autonomy and capabilities, which increases the risk that a misaligned AI may be able to cause catastrophic harm. Untrus…
- arXiv cs.AIagentsSTRUCTUREDAGENT: Planning with AND/OR Trees for Long-Horizon Web Tasks
arXiv:2603.05294v3 Announce Type: replace Abstract: Existing LLM-based web agents struggle on complex, long-horizon tasks due to limited in-context memory, weak planning abilities, and greedy behaviors that lead to prema…
- arXiv cs.AIresearchSocialOmni: Benchmarking Audio-Visual Social Interactivity in Omni Models
arXiv:2603.16859v3 Announce Type: replace Abstract: Evaluating omni-modal large language models (OLMs) in multi-party dialogue requires more than answer correctness on pre-segmented inputs. We introduce SocialOmni, an of…
- arXiv cs.AIresearchToward an automated science of the mind
arXiv:2603.20988v2 Announce Type: replace Abstract: Artificial Intelligence is starting to automate scientific discovery, raising the prospect of an automated science of the mind. We chart this field around four challeng…
- arXiv cs.AIagentsThe Self Driving Portfolio: Agentic Architecture for Institutional Asset Management
arXiv:2604.02279v2 Announce Type: replace Abstract: Agentic AI shifts the investor's role from analytical execution to oversight. We present an agentic strategic asset allocation pipeline in which 44 specialized agents p…
- arXiv cs.AIagentsCivBench: Progress-Based Evaluation for LLMs' Strategic Decision-Making in Civilization V
arXiv:2604.07733v2 Announce Type: replace Abstract: Evaluating strategic decision-making in LLM-based agents requires generative, competitive, and longitudinal environments, yet few benchmarks provide all three, and fewe…
- arXiv cs.AIresearchCharacterizing Model-Native Skills
arXiv:2604.17614v2 Announce Type: replace Abstract: Skills are a natural unit for describing what a language model can do and how its behavior can be changed. However, existing characterizations rely on human-written tax…
- arXiv cs.AIresearchInformation-Geometric First-Passage Monitoring of Distributional Stability in Stochastic Systems
arXiv:2604.24083v2 Announce Type: replace Abstract: Runtime monitoring of stochastic systems must distinguish nominal distributional relaxation from regime departure while controlling repeated-test false alarms under exp…
- arXiv cs.AIagentsAn Analysis of the Coordination Gap between Joint and Modular Learning for Job Shop Scheduling with Transportation Resources
arXiv:2604.24117v3 Announce Type: replace Abstract: Efficient job-shop scheduling with transportation resources is critical for high-performance manufacturing. With the rise of "decentralized factories", multi-agent rein…
- arXiv cs.AIresearchTaming the Centaur(s) with LAPITHS: a framework for a theoretically grounded interpretation of AI performances
arXiv:2604.27927v2 Announce Type: replace Abstract: We introduce a framework called LAPITHS (Language model Analysis through Paradigm grounded Interpretations of Theses about Human likenesS) and use it to show that sever…
- arXiv cs.AIagentsCoFlow: Coordinated Few-Step Flow for Offline Multi-Agent Decision Making
arXiv:2605.01457v4 Announce Type: replace Abstract: How can generative offline multi-agent reinforcement learning achieve both fast joint trajectory generation and effective cooperation? Multi-agent diffusion models gene…
- arXiv cs.AIresearchRankQ: Offline-to-Online Reinforcement Learning via Self-Supervised Action Ranking
arXiv:2605.11151v4 Announce Type: replace Abstract: Offline-to-online reinforcement learning (RL) improves sample efficiency by leveraging pre-collected datasets prior to online interaction. A key challenge, however, is…
- arXiv cs.AIagentsToolCUA: Towards Optimal GUI-Tool Path Orchestration for Computer Use Agents
arXiv:2605.12481v2 Announce Type: replace Abstract: Computer Use Agents (CUAs) can act through both atomic GUI actions, such as click and type, and high-level tool calls, such as API-based file operations, but this hybri…
- arXiv cs.AIresearchTTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens
arXiv:2605.16638v2 Announce Type: replace Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this paradigm, a generative…
- arXiv cs.AIagentsReliability and Effectiveness of Autonomous AI Agents in Supply Chain Management
arXiv:2605.17036v4 Announce Type: replace Abstract: This paper studies the performance and reliability of autonomous generative AI agents in multi-echelon supply chains using the MIT Beer Game. We examine how model choic…
- arXiv cs.AIresearchRubric-Guided Process Reward for Stepwise Model Routing
arXiv:2605.29310v2 Announce Type: replace Abstract: Stepwise model routing improves the efficiency of Large Reasoning Models (LRMs) by assigning each reasoning step to a suitable model. Recent methods formulate routing a…
- arXiv cs.AIagentsPTCG-Bench: Can LLM Agents Master Pok\'emon Trading Card Game?
arXiv:2605.29653v2 Announce Type: replace Abstract: Given a strategically complex board game, human players can quickly learn to devise strategies after playing a few rounds. Autonomous agents require similar capabilitie…
- arXiv cs.AIagentsCan Generalist Agents Automate Data Curation?
arXiv:2606.04261v2 Announce Type: replace Abstract: Curating training data is among the most consequential yet labor-intensive parts of modern AI development: practitioners iteratively propose, implement, evaluate, and r…
- arXiv cs.AIagentsHow Far Did They Go? The Persuasive Tactics of Covert LLM Agents in a Discontinued Field Experiment
arXiv:2606.05256v2 Announce Type: replace Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView. The intervention, conducted by unknown, external resear…
- arXiv cs.AIresearchRedKnot: Efficient Long-Context LLM Serving with Head-Aware KV Reuse and SegPagedAttention
arXiv:2606.06256v4 Announce Type: replace Abstract: As the input length of large language model (LLM) serving continues to grow, the KV cache has become a dominant bottleneck in AI infrastructure. It limits GPU memory ca…
- arXiv cs.AIagentsDecision-Aware Memory Cards: Counterfactual-Inspired Context Selection and Compression for Tool-Using LLM Agents
arXiv:2606.08151v4 Announce Type: replace Abstract: Modern large language model (LLM) agents do not simply need longer contexts; they need decision-relevant evidence at the moment of action. We study decision-aware conte…
- arXiv cs.AIagentsTo Nuke or Not to Nuke: LLMs' (Missing) Ethical Reasoning and Actions in a High-Stakes Decision-Making Simulation
arXiv:2606.08310v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as long-horizon agents with decision-making capacities. While LLMs can show ethical competence on dilemmas such a…
- arXiv cs.AIagentsMDForge: Agentic Molecular Dynamics Pipeline Design under Sparse Simulator Feedback
arXiv:2606.12916v2 Announce Type: replace Abstract: Molecular dynamics (MD) is the canonical in-silico method for atomistic molecular science, simulating molecular behavior from first-principle physics. Designing an MD p…
- arXiv cs.AIagentsENPIRE: Agentic Robot Policy Self-Improvement in the Real World
arXiv:2606.19980v2 Announce Type: replace Abstract: Achieving dexterous robotic manipulation in the real world heavily relies on human supervision and algorithm engineering, which becomes a central bottleneck in the purs…
- arXiv cs.AIresearchA General Multimodal Probing Framework for Data Fusion and Prediction with Frozen Large Language Models: Evidence from Multimodal EHR Data
arXiv:2606.28798v2 Announce Type: replace Abstract: The main objective of this paper is to propose a general framework for prediction based on different sources of multimodal data in the healthcare domain. We evaluated w…
- arXiv cs.AIagentsScoped Verification for Reliable Long-Horizon Agentic Context Evolution under Distribution Shift
arXiv:2607.09175v2 Announce Type: replace Abstract: Deployed LLM agents rely on agentic context, the model-external textual control content assembled by an operational harness. In this work, the mutable component of that…
- arXiv cs.AIresearchLength Penalties Make Chain-of-Thought Less Monitorable
arXiv:2607.09786v4 Announce Type: replace Abstract: Recent work trains reasoning models with length penalties to curb overthinking and cut inference cost. We show that these penalties make the chain of thought less monit…