AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchAn Analysis of Artificial Intelligence Adoption in NIH-Funded Research
arXiv:2604.07424v2 Announce Type: replace Abstract: Understanding the landscape of artificial intelligence (AI) and machine learning (ML) adoption across the National Institutes of Health (NIH) portfolio is critical for…
- arXiv cs.AIagentsExploration and Exploitation Errors Are Measurable for Language Model Agents
arXiv:2604.13151v2 Announce Type: replace Abstract: Language Model (LM) agents are increasingly used in complex decision-making tasks, from AI coding to physical AI, where they must both explore a search space and exploi…
- arXiv cs.AIresearchTowards Training Transformers as a Universal Computer
arXiv:2604.25166v2 Announce Type: replace Abstract: We demonstrate that a small transformer can learn to execute programs in MicroPy, a simplified yet computationally universal programming language. Given procedure defin…
- arXiv cs.AIagentsAEM: Adaptive Entropy Modulation for Multi-Turn Agentic Reinforcement Learning
arXiv:2605.00425v4 Announce Type: replace Abstract: Reinforcement learning (RL) has substantially improved the ability of large language model (LLM) agents to interact with environments and solve multi-turn tasks. Howeve…
- arXiv cs.AIagentsWhen Stored Evidence Stops Being Usable: Scale-Conditioned Evaluation of Agent Memory
arXiv:2605.07313v2 Announce Type: replace Abstract: Memory-agent evaluations report fixed-snapshot accuracy or retrieval quality, but these scores do not show whether evidence remains usable as irrelevant sessions (sessi…
- arXiv cs.AIagentsRobust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning
arXiv:2605.12655v4 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) in real-world use cases may need to adapt to external natural language instructions that interrupt ongoing behavior and confli…
- arXiv cs.AIresearchLearning Mental Models From Unreliable Evidence
arXiv:2605.24528v3 Announce Type: replace Abstract: Children expertly construct mental models under uncertainty despite limited world knowledge. Which computational principles make this possible? We study this question i…
- arXiv cs.AIresearchForget Attention: Importance-Aware Attention Is All You Need
arXiv:2606.02332v3 Announce Type: replace Abstract: Attention retrieves content precisely, but its scores depend only on query--key products, leaving order and recency to positional encodings. Conversely, state-space mod…
- arXiv cs.AIagentsINFRAMIND: Infrastructure-Aware Multi-Agent Orchestration
arXiv:2606.11440v2 Announce Type: replace Abstract: Multi-agent LLM systems spend additional computation on reasoning and collaboration, but shared serving queues can prevent that computation from producing answers befor…
- arXiv cs.AIresearchDifference-Making without Making a Difference
arXiv:2606.24832v2 Announce Type: replace Abstract: Over a series of seven papers, Andreas & G\"unther have introduced seven definitions of actual causation and have classified them as belonging to three different, compe…
- arXiv cs.AIresearchFrom Profiles to Steering Vectors: Global Sparse Priors and Local Semantic Calibration for Personalized Text Generation
arXiv:2607.21620v2 Announce Type: replace Abstract: Personalized text generation requires models to capture user-specific writing styles from historical data. Existing approaches based on retrieval, parameter-efficient f…
- arXiv cs.AIresearchWNM-3D: A World Navigation Model with 3D Scene Conditioning for Closed-Loop VLN
arXiv:2608.07267v3 Announce Type: replace Abstract: Recent vision-language navigation (VLN) systems increasingly adapt pretrained vision-language models (VLMs) into vision-language-action (VLA) policies that map egocentr…
- arXiv cs.AIresearchDiG-bench: Discovery in Games
arXiv:2608.12593v2 Announce Type: replace Abstract: Discovery---formulating novel generalizations---is a central part of the scientific process. Despite its importance, there is a gap in the current AI benchmark landscap…
- arXiv cs.AIresearchProcess-Constituted Intelligence: A Shared Criterion for Humans and Machines
arXiv:2608.16213v3 Announce Type: replace Abstract: Intelligence is constituted by \textit{process} (iterative activity through which output emerges), not in the output itself. Generative AI (GenAI) is trained on \textit…
- arXiv cs.AIagentsPoisoning Agentic Alpha: Adversarial Vulnerabilities Across Roles and Architectures in Multi-Agent Trading Systems
arXiv:2608.24069v2 Announce Type: replace Abstract: LLM-based multi-agent trading systems are moving from research prototypes to live deployments that control real assets. They ingest news and social media from the open…
- arXiv cs.AIagentsRePolicy: Learning to Select and Apply Safety Policies for Agent Safeguards
arXiv:2608.24275v3 Announce Type: replace Abstract: Agent safeguards must determine whether an agent's behavior violates the safety rules of the current task, environment, and user. Because these rules vary across contex…
- arXiv cs.AIresearchLLM-Driven, Datasheet-Aware Automated Hardware Compatibility Verification for Early-Stage, Pre-Schematic Embedded System Design
arXiv:2608.25217v2 Announce Type: replace Abstract: We present an LLM-driven, datasheet-aware framework for early-stage hardware compatibility verification that identifies documentation-level interface incompatibilities…
- arXiv cs.AIagentsATLAS: Dual-Horizon Diagnostic Evaluation for Tool-Use Agents in Meituan Xiaotua
arXiv:2608.30685v2 Announce Type: replace Abstract: LLM-based assistants on web-scale service platforms increasingly address local-service needs through multi-step planning and tool use. Under dynamic business conditions…
- arXiv cs.AIagentsVoiceLongMemEval: Do Assistants Remember How You Sounded?
arXiv:2609.00570v3 Announce Type: replace Abstract: With the growing scale of multi-agent architectures and large language models, deployed AI assistants are increasingly tasked with reasoning over long, continuous, mult…
- arXiv cs.AIresearchEpistemic Warrant for LLM Recommendations: Characterizing the Basis for Reliance When Ground Truth Is Unavailable
arXiv:2609.04127v2 Announce Type: replace Abstract: Large language models are increasingly used to support organizational decisions. Despite their rapid and widespread adoption, users often lack a principled basis for as…
- arXiv cs.AIresearchNovGauge: A Fine-Grained Benchmark for Diagnosing LLMs' Capability in Paper Novelty Assessment
arXiv:2609.11234v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchmarks assess novel…
- arXiv cs.AIagentsGeneralized Agent Iteration: One Formal Framework for Iterative Policy Improvement and Recursive Self-Improvement
arXiv:2609.13406v2 Announce Type: replace Abstract: When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intelligence, RSI is bei…
- arXiv cs.AIagentsEvaluation Metrics for Safe Reinforcement Learning
arXiv:2609.15315v2 Announce Type: replace Abstract: Safe reinforcement learning (RL) is commonly formalized as a Constrained Markov Decision Process (CMDP), in which an agent maximizes expected reward while keeping its e…
- arXiv cs.AIagentsWorld Model Science: Self-Organized Criticality, Weak Chaos, and Metastable Belief Dynamics in Long-Horizon LLM Agents
arXiv:2609.17419v2 Announce Type: replace Abstract: Long-horizon LLM agents must maintain and update a world model over extended sequences of observations, actions, decisions and tool calls. We study the dynamics of long…
- arXiv cs.AIresearchStrategic Integration of Artificial Intelligence in the C-Suite: The Role of the Chief AI Officer
arXiv:2407.10247v4 Announce Type: replace-cross Abstract: The integration of Artificial Intelligence (AI) into corporate strategy has become critical for organizations seeking to maintain competitive advantage in the dig…
- arXiv cs.AIagentsExact Algorithms for Multiagent Path Finding with Communication Constraints on Tree-Like Structures
arXiv:2412.08556v4 Announce Type: replace-cross Abstract: Consider the scenario where multiple agents have to move in an optimal way through a network, each one towards their ending position while avoiding collisions. By…
- arXiv cs.AIagentsAligned Delta-Triplane Transformers as Occupancy World Models
arXiv:2503.07338v5 Announce Type: replace-cross Abstract: Occupancy World Models (OWMs) aim to predict future 3D occupancy scenes from historical observations and future ego motions, providing a useful world simulation t…
- arXiv cs.AIresearchJoint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment
arXiv:2505.07852v2 Announce Type: replace-cross Abstract: Detecting fake interactions in digital communication platforms remains a challenging and insufficiently addressed problem. These interactions may appear as harmle…
- arXiv cs.AIresearchTrustworthy AI and Democracy: A Dual Taxonomy and Operational Framework of Democratic Risks and Contributions
arXiv:2505.13565v3 Announce Type: replace-cross Abstract: Artificial Intelligence (AI) can undermine and strengthen democratic governance. This paper introduces the AIRD/AIPD framework, a dual taxonomy and operational fr…
- arXiv cs.AIresearchGeneralizable dose denoising using diffusion transformer framework for pencil beam scanning proton therapy
arXiv:2506.04467v2 Announce Type: replace-cross Abstract: Background and purpose: Intensity-modulated proton therapy (IMPT) enables conformal dose delivery for head and neck (H&N) cancers. However, its sensitivity to int…
- arXiv cs.AIresearchRethinking Group Recommender Systems in the Era of Generative AI: From One-Shot Recommendations to Conversational Group Decision Support
arXiv:2507.00535v3 Announce Type: replace-cross Abstract: More than twenty-five years ago, early ideas emerged on how to design systems that provide recommendations to groups of users rather than individuals. Since then,…
- arXiv cs.AIagentsThe Algorithm Is Not the Behavior: Learned Priors Override Look-Ahead in a Chess-Playing Neural Network
arXiv:2508.21380v4 Announce Type: replace-cross Abstract: Recent mechanistic work has uncovered learned algorithms within neural networks, from modular arithmetic to search and planning in game-playing agents. But does a…
- arXiv cs.AIresearchMembership Inference Attacks on Recommender System: A Survey
arXiv:2509.11080v5 Announce Type: replace-cross Abstract: Recommender systems (RecSys) have been widely applied to various applications, including E-commerce, finance, healthcare, social media and have become increasingl…
- arXiv cs.AIresearchAttribution Gradients: Incrementally Unfolding Citations for Critical Examination of Attributed AI Answers
arXiv:2510.00361v3 Announce Type: replace-cross Abstract: AI answer engines are a relatively new kind of information search tool: rather than returning a ranked list of documents, they generate an answer to a search ques…
- arXiv cs.AIresearchNeuroBridge: Bio-Inspired Self-Supervised EEG-to-Image Decoding via Cognitive Priors and Bidirectional Semantic Alignment
arXiv:2511.06836v2 Announce Type: replace-cross Abstract: Visual neural decoding seeks to reconstruct or infer perceived visual stimuli from brain activity patterns, providing critical insights into human cognition and e…
- arXiv cs.AIresearchPepEVOLVE: Position-Aware Dynamic Peptide Optimization via Group-Relative Advantage
arXiv:2511.16912v2 Announce Type: replace-cross Abstract: Macrocyclic peptides are an emerging modality that combines biologics-like affinity with small-molecule-like developability, yet their vast combinatorial space an…
- arXiv cs.AIagentsDualGauge: Automated Joint Security-Functionality Benchmarking of Specification-Only Code Generation by LLMs and Coding Agents
arXiv:2511.20709v3 Announce Type: replace-cross Abstract: Large language models (LLMs) and LLM-based coding agents are now used to generate code from natural-language specifications, yet ensuring such code is both functi…
- arXiv cs.AIresearchMedGemma vs GPT-4: Open-Source and Proprietary Zero-shot Medical Disease Classification from Images
arXiv:2512.23304v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (LLMs) introduce an emerging paradigm for medical imaging by interpreting scans through the lens of extensive clinical knowledge,…
- arXiv cs.AIresearchReferential Regimes: Transformation-Based Identity Profiles for Neutral Substrates
arXiv:2601.16152v3 Announce Type: replace-cross Abstract: Data systems operating under persistent legal, institutional, and analytic disagreement require shared reference without presupposing agreement about interpretati…
- arXiv cs.AIresearchJacobian Scopes: A Unified Geometric Framework for Token-Level LLM Attribution
arXiv:2601.16407v5 Announce Type: replace-cross Abstract: Large language models (LLMs) make next-token predictions based on clues present in their context, such as semantic descriptions and in-context examples. Yet, eluc…
- arXiv cs.AIresearchIndustrialized Deception: The Collateral Effects of LLM-Generated Misinformation on Digital Ecosystems
arXiv:2601.21963v3 Announce Type: replace-cross Abstract: Generative AI and misinformation research have evolved since our 2024 survey. This paper presents an updated perspective, transitioning from literature review to…
- arXiv cs.AIresearchClueTracer: Question-to-Vision Clue Tracing for Training-Free Hallucination Suppression in Multimodal Reasoning
arXiv:2602.02004v2 Announce Type: replace-cross Abstract: Large multimodal reasoning models solve challenging visual problems via explicit long-chain inference: they gather visual clues from images and decode clues into…
- arXiv cs.AIresearchThe Verification Crisis: Expert Perceptions of GenAI Disinformation and the Case for Reproducible Provenance
arXiv:2602.02100v2 Announce Type: replace-cross Abstract: The growth of Generative Artificial Intelligence (GenAI) has shifted disinformation production from manual fabrication to automated, large-scale manipulation. Thi…
- arXiv cs.AIresearchRethinking Bayesian Optimization for Co-Optimizing LLM Training Configurations
arXiv:2602.08351v3 Announce Type: replace-cross Abstract: Fine-tuning an LLM to maximize performance on a downstream task requires finding the optimal data and model configuration. This is a black-box optimization proble…
- arXiv cs.AIagentsAnagent For Enhancing Scientific Table & Figure Analysis
arXiv:2602.10081v3 Announce Type: replace-cross Abstract: In scientific research, analysis requires accurately interpreting complex multimodal knowledge, integrating evidence from different sources, and drawing inference…
- arXiv cs.AIresearchRobust Taylor-Lagrange Control for Safety-Critical Systems with Guaranteed Feasibility
arXiv:2602.20076v2 Announce Type: replace-cross Abstract: The Control Barrier Function (CBF) method has been widely adopted in solving safety-critical control problems. However, the existence of a CBF is only a sufficien…
- arXiv cs.AIresearchA general extractor for coherent patterns across time-frequency measurements
arXiv:2602.20317v3 Announce Type: replace-cross Abstract: Scientific discovery increasingly depends on finding meaningful patterns within volumes of sensor data too large for manual inspection. Existing time-frequency ev…
- arXiv cs.AIresearchExplainability-Aware Evaluation of Transfer Learning Models for IoT DDoS Detection Under Resource Constraints
arXiv:2602.22488v2 Announce Type: replace-cross Abstract: Distributed denial of service (DDoS) attacks threaten the availability of Internet of Things (IoT) infrastructures, particularly under resource-constrained deploy…
- arXiv cs.AIresearchNo Certificate, No Categorical Speech Act: A Brouwerian Assertibility Constraint for Public Reason
arXiv:2603.03971v5 Announce Type: replace-cross Abstract: Generative AI can convert uncertainty into authoritative-seeming verdicts, displacing the justificatory work on which democratic epistemic agency depends. As a co…
- arXiv cs.AIresearchTowards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
arXiv:2603.08588v3 Announce Type: replace-cross Abstract: State-of-the-art deep reinforcement learning (RL) methods have achieved remarkable performance in continuous control tasks, yet their computational complexity is…