AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchAVC-Reward: Event-Centric Audio-Video Consistency Evaluation
arXiv:2610.22321v1 Announce Type: cross Abstract: As joint audio-video generation models become more capable, they can generate audio-visual scenes exhibiting three forms of complexity: multi-event composition, multi-lay…
- arXiv cs.AIagentsLearning Self-Orchestration in Decentralized Agent Swarms
arXiv:2610.22322v2 Announce Type: replace-cross Abstract: The capabilities of an agent swarm depend on both its individual members and how they coordinate. Yet existing multi-agent systems often train agents within fixed…
- arXiv cs.AIresearchTwice Upon a Time: Complementary Representations for Time-Series Reasoning
arXiv:2610.22327v1 Announce Type: cross Abstract: Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what information should thei…
- arXiv cs.AIresearchACEdit: Stable Multi-Turn Image Editing via Asymmetric Conditioning
arXiv:2610.22328v1 Announce Type: cross Abstract: Image editing models produce impressive results for individual edits, but their quality often deteriorates over multiple editing turns. Each editing turn introduces small…
- arXiv cs.AIagentsPlayPolicy: Dexterity from Supervised Play
arXiv:2610.22340v2 Announce Type: replace-cross Abstract: How can robots autonomously collect the contact-rich experience needed to learn dexterous manipulation? We present PlayPolicy: Dexterity from supervised play (DSP…
- arXiv cs.AIagents3DCodeVerse: Exploring 3D Worlds as Code
arXiv:2610.22341v1 Announce Type: cross Abstract: We introduce 3DCodeVerse, a research ecosystem that enables coding agents to create editable and verifiable 3D content at scale. 3DCodeVerse comprises large-scale, high-q…
- arXiv cs.AIresearchGeoState: Learning View-Decoupled Geometry States for 3D World Modeling
arXiv:2610.22343v1 Announce Type: cross Abstract: Recent 3D world models increasingly use features from geometry foundation models (GFMs) as predictive world states, benefiting from their rich geometric priors. However,…
- arXiv cs.AIresearchRethinking Routing Exploration in Modern Mixture-of-Experts
arXiv:2610.22353v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models have become an important approach for scaling model parameters. Modern MoE architectures increasingly combine two design choices: fine-gra…
- arXiv cs.AIresearchCoDA: Co-Evolution of Data Engines and Action Policies
arXiv:2610.22362v1 Announce Type: cross Abstract: Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training. The challenge is to identify…
- arXiv cs.AIresearchT2-z: Test-Time Optimization of Environment Latents for Robotic World Models
arXiv:2610.22364v1 Announce Type: cross Abstract: Predicting how the world responds to an action requires more than what can be seen: robots must account for environmental factors that are neither directly observable nor…
- arXiv cs.AIresearchDiscovering state-of-the-art quantum circuits with large language models
arXiv:2610.22367v1 Announce Type: cross Abstract: Significant efforts are currently being directed toward the implementation of large-scale quantum information processors, but realizing useful quantum advantage also requ…
- arXiv cs.AIresearchLIBERO-PeRM: Benchmarking Personalized Robotic Manipulation
arXiv:2610.22372v1 Announce Type: cross Abstract: Personalization is essential for general-purpose robots to transition into household environments and achieve true practicality. While general robotic manipulation has be…
- arXiv cs.AIresearchAtomic Proximal Policy Optimization for Electric Robo-Taxi Dispatch and Charger Allocation
arXiv:2502.13392v3 Announce Type: replace Abstract: Pioneering companies such as Waymo have deployed electric robo-taxi services in several U.S. cities. Operating such fleets requires coordinating ride matching, vehicle…
- arXiv cs.AIresearchGraphCompliance: Structure-Aware Regulatory Compliance through Policy-Context Graph Alignment
arXiv:2510.26309v2 Announce Type: replace Abstract: Regulatory compliance is an important requirement in many industrial and administrative settings. Yet compliance assessment remains difficult because regulatory require…
- arXiv cs.AIresearchChaosBench-Logic: A Benchmark for Logical and Symbolic Reasoning on Chaotic Dynamical Systems
arXiv:2601.01982v2 Announce Type: replace Abstract: Large language models (LLMs) excel at natural language tasks but remain brittle in domains requiring precise logical and symbolic reasoning. Chaotic dynamical systems p…
- arXiv cs.AIagentsAgent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments
arXiv:2602.16653v4 Announce Type: replace Abstract: Skills are getting increasingly used in recent agentic frameworks, performing robustly with proprietary LLMs. Yet, their effectiveness for small and medium-sized open-s…
- arXiv cs.AIresearchJEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures
arXiv:2602.17162v4 Announce Type: replace Abstract: Genomic Foundation Models (GFMs) typically rely on Masked Language Modeling (MLM) or Next-Token Prediction (NTP) to learn the "Laws of Nature". While effective at captu…
- arXiv cs.AIagentsWorkflowPerturb: Calibrated Stress Tests for Evaluating Multi-Agent Workflow Metrics
arXiv:2602.17990v4 Announce Type: replace Abstract: Multi-agent LLM systems that generate structured workflows from natural-language requests are now deployed in production across cloud automation, DevOps, and enterprise…
- arXiv cs.AIresearchTowards Better Aligned LLM Judges for Radiology Report Evaluation across Modalities and Anatomies
arXiv:2604.03376v2 Announce Type: replace Abstract: Current work on radiology report evaluation has focused primarily on LLM-based metrics for chest X-rays (CXR), leaving open whether such approaches remain robust across…
- arXiv cs.AIresearchLanguage models recognize dropout and Gaussian noise applied to their activations
arXiv:2604.17465v3 Announce Type: replace Abstract: We provide evidence that language models can detect, localize and, to a degree, verbalize the difference between a-semantic perturbations applied to their activations.…
- arXiv cs.AIagentsSelf-Programmed Execution for Language-Model Agents
arXiv:2605.06898v2 Announce Type: replace Abstract: At the heart of a language model agent is an orchestrator program which is responsible for the state transition between consecutive turns. In existing systems, this pro…
- arXiv cs.AIagentsPREPING: Zero-Task Agent Memory Construction via Self-Practice
arXiv:2605.13880v2 Announce Type: replace Abstract: Agent memory is typically constructed either offline from curated demonstrations or online from post-deployment interactions. However, regardless of how it is built, an…
- arXiv cs.AIagentsProspective multi-pathogen disease forecasting using autonomous LLM-guided tree search
arXiv:2605.16238v2 Announce Type: replace Abstract: Probabilistic forecasting of infectious diseases is crucial for public health monitoring and preparedness but has historically relied on labor-intensive manual model cu…
- arXiv cs.AIagentsAdapting the Interface, Not the Model: Runtime Harness Adaptation for Deterministic LLM Agents
arXiv:2605.22166v3 Announce Type: replace Abstract: LLM agents are shaped not only by their language models, but also by the runtime harness that mediates observation, tool use, action execution, feedback interpretation,…
- arXiv cs.AIresearchPathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning
arXiv:2605.23074v2 Announce Type: replace Abstract: Large Reasoning Language Models (LRMs) tackle complex tasks through test-time scaling, generating long-form Chain-of-Thought (CoT) trajectories during inference. These…
- arXiv cs.AIagentsHarness-Bench: Evaluating Agent Harnesses across Models and Realistic Workflows
arXiv:2605.27922v2 Announce Type: replace Abstract: LLM agents are increasingly deployed as executable systems that use tools, modify workspaces, and produce concrete artifacts. In such workflows, performance depends not…
- arXiv cs.AIresearchKACE: Knowledge-Adaptive Context Engineering for Mathematical Reasoning
arXiv:2606.00532v2 Announce Type: replace Abstract: Context-engineering methods improve a frozen language model by learning text from execution feedback and placing it in the prompt. When one learned prompt carries every…
- arXiv cs.AIagentsSkillDAG: Self-Evolving Typed Skill Graphs for LLM Skill Selection at Scale
arXiv:2606.03056v3 Announce Type: replace Abstract: Large skill libraries are now standard equipment for LLM agents, and which subset reaches the prompt decides what the agent can do. Enumeration and top-$K$ embedding re…
- arXiv cs.AIagentsEvoFlux: Inference-Time Evolution of Executable Tool Workflows for Compact Agents
arXiv:2606.12674v2 Announce Type: replace Abstract: Small language models (1.5B-4B parameters) offer low-cost, low-latency tool use but often produce plausible plans that fail during execution due to unavailable tools, m…
- arXiv cs.AIagentsLLM-as-an-Investigator: Evidence-First Agentic Reasoning for Robust Interactive Problem Diagnosis
arXiv:2606.13220v2 Announce Type: replace Abstract: Large language models (LLMs) are used for technical troubleshooting, where problem descriptions are often incomplete and multiple causes can explain the same symptoms.…
- arXiv cs.AIagentsMulti-Agent Transactive Memory
arXiv:2606.19911v2 Announce Type: replace Abstract: Decentralized deployment of LLM agents with diverse capabilities motivates infrastructure for knowledge sharing across heterogeneous agent populations. Just as search e…
- arXiv cs.AIresearchAI Alignment From Social Choice Perspectives
arXiv:2606.21550v2 Announce Type: replace Abstract: Alignment from human feedback uses human judgments about model outputs to steer the behavior of language models after pretraining. When those judgments reflect conflict…
- arXiv cs.AIresearchMind the Delay: Latency-aware Query Routing for Heterogeneous LLM pools
arXiv:2607.18253v2 Announce Type: replace Abstract: Large language model (LLM) query routers typically assign each query to a suitable model that balances response accuracy and monetary cost. Subsequently, separate syste…
- arXiv cs.AIresearchAI and Consumer Rights in India Working Paper
arXiv:2608.12863v2 Announce Type: replace Abstract: As AI systems proliferate in consumer facing applications, questions about liability for AI related harms remain unresolved. This working paper examines whether India's…
- arXiv cs.AIresearchWhen Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning
arXiv:2608.14610v2 Announce Type: replace Abstract: Legal reasoning requires identifying which version of a statute applies to a case, typically based on when the legally relevant events occurred rather than when the cas…
- arXiv cs.AIagentsAgent Gym: A Framework for Continuous Evaluation and Evolution of LLM Agents Through Human-in-the-Loop Feedback
arXiv:2608.15591v2 Announce Type: replace Abstract: Large Language Model (LLM) agents deployed in production environments face a fundamental tension: the agent's behavior is frozen at deployment time, while the business…
- arXiv cs.AIagentsMegaMem: A Retrieval Solution for Ultra-Large Context Windows
arXiv:2608.22137v2 Announce Type: replace Abstract: Modern language models and agents increasingly require persistent memory for complete codebases, long interaction histories, and heterogeneous enterprise records. The k…
- arXiv cs.AIresearchMEMONDEMAND: A Memory Management System for Large-Scale Enterprise Data
arXiv:2608.22141v2 Announce Type: replace Abstract: Enterprise repositories are large, heteroge- neous, and continuously updated, making re- trieval difficult when efficient access, source- faithful evidence, and cross-q…
- arXiv cs.AIresearchDesign the Feedback, Not Just the Reward: Environments for Open-Ended Reinforcement Learning
arXiv:2608.27906v4 Announce Type: replace Abstract: Reinforcement learning has advanced large language models on tasks with reliable verifiers, where checking an outcome provides a clear basis for reward. Extending this…
- arXiv cs.AIresearchBLOOM-WILT: Logit Tilting for Behaviour Elicitation in Automated LLM Auditing
arXiv:2608.31105v2 Announce Type: replace Abstract: Users of a deployed language model routinely encounter behaviours that have never been observed during testing, since deployment puts the model through orders of magnit…
- arXiv cs.AIresearchTask-Level Natural Language Priors as Learning Signals for Low-Resource LLM Training
arXiv:2609.02244v2 Announce Type: replace Abstract: Large language models (LLMs) often struggle when low-resource training data are ambiguous or incomplete. Task-level natural-language priors can provide useful guidance…
- arXiv cs.AIagentsConstructing and Evaluating Clinical Reasoning Trajectories for Medical Agent
arXiv:2609.05090v2 Announce Type: replace Abstract: Evaluation of medical artificial intelligence agents remains predominantly answer-centric, assessing only the correctness of final outputs while overlooking the quality…
- arXiv cs.AIagentsCABAL: Multi-Agent Simulacra for Tracing the Effects of Collusive Bidding in Peer Review
arXiv:2609.05227v3 Announce Type: replace Abstract: Recent reports during the AAAI-27 review cycle highlight the risk of reviewers coordinating bids for reciprocal assignment advantage. Prior work treats bidding, reviewe…
- arXiv cs.AIagentsFrom Simulated Citizens to Simulated Deliberation: Challenges in Representation and Interaction
arXiv:2609.07573v2 Announce Type: replace Abstract: Can LLM agents simulate how a real public would deliberate? For such simulations to be meaningful, agents must reflect the population's opinions, and their views must b…
- arXiv cs.AIresearchT-GADE: Thermodynamical Generative-AI-Driven Evolution of LLM Artifacts
arXiv:2609.12286v2 Announce Type: replace Abstract: Introducing large language models (LLMs) into evolutionary computation enables semantic generation of candidates, but the classical problem of maintaining population di…
- arXiv cs.AIresearchDistributionally Robust Regularization of Sparse Integer Programming Trained Learning Models
arXiv:2311.01994v2 Announce Type: replace-cross Abstract: Building explainable machine learning models is crucial for human users to be able to interpret the proposed statistical relationship obtained from the training d…
- arXiv cs.AIresearchInkSight: Offline-to-Online Handwriting Conversion by Teaching Vision-Language Models to Read and Write
arXiv:2402.05804v5 Announce Type: replace-cross Abstract: Digital note-taking is gaining popularity, offering a durable, editable, and easily indexable way of storing notes in a vectorized form, known as digital ink. How…
- arXiv cs.AIresearchPairwise Difference Learning for Classification
arXiv:2406.20031v2 Announce Type: replace-cross Abstract: Pairwise difference learning (PDL) has recently been introduced as a new meta-learning technique for regression. Instead of learning a mapping from instances to o…
- arXiv cs.AIresearchLLMR: Knowledge Distillation with a Large Language Model-Induced Reward
arXiv:2409.12500v2 Announce Type: replace-cross Abstract: Large language models have become increasingly popular and demonstrated remarkable performance in various natural language processing (NLP) tasks. However, these…
- arXiv cs.AIresearchSTAMP: Symmetric Temporal Averaging Message Passing for Domain Adaptation in Chronologically Split Graphs
arXiv:2411.10957v2 Announce Type: replace-cross Abstract: This paper addresses domain adaptation in graph-structured data under chronological splits. We consider transductive semi-supervised node classification (SSNC), i…