AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchNutriVision: Ingredient-Conditioned Fusion and Prediction for Single-Image Food Nutrition Estimation
arXiv:2609.33076v2 Announce Type: replace-cross Abstract: Nutrition estimation is a fundamental task in consumer diet tracking, clinical dietetics, chronic disease management, sports and hospital nutrition, and broader f…
- arXiv cs.AIresearchSemReward-VL: Semantic Reward-Guided Video-Language Adaptation for Developmental Behavior Assessment
arXiv:2609.33082v1 Announce Type: cross Abstract: Developmental screening videos show how children perform specific behaviors, but clinical records usually contain outcomes rather than descriptions of what happened. We p…
- arXiv cs.AIresearchOneSign: Unifying Sign Language Understanding Tasks with One Model
arXiv:2609.33090v1 Announce Type: cross Abstract: SLU encompasses a diverse set of tasks, including ISLR, CSLR, and SLT. Although these tasks share basic semantic and linguistic foundations, they are typically addressed…
- arXiv cs.AIresearchHow Linear Attention Remembers
arXiv:2609.33093v1 Announce Type: cross Abstract: Linear attention replaces the growing key--value (KV) cache of standard attention with a fixed-size recurrent state, substantially reducing memory growth with context len…
- arXiv cs.AIresearchQuery, Align, and Distill: Navigation-Aware Cross-Modal Interaction for Efficient Vision-and-Language Navigation
arXiv:2609.33097v1 Announce Type: cross Abstract: Recent large-scale Vision-and-Language Navigation (VLN) models deliver strong accuracy but remain costly to deploy due to their large parameter counts and computational r…
- arXiv cs.AIresearchVPTwin: Real-Sim-Real Video Prediction for Robotic Manipulation Planning
arXiv:2609.33104v1 Announce Type: cross Abstract: While action-conditioned video prediction provides an intuitive world model for robotics, purely data-driven predictors often suffer from compounding errors and physicall…
- arXiv cs.AIresearchToward Comprehensive 3D Grounding: Orientation Grounding through Vision-Language Models
arXiv:2609.33109v1 Announce Type: cross Abstract: Grounding is a core capability of spatial vision-language models, yet most existing work focuses only on where a referred object is. Many 3D tasks also require knowing ho…
- arXiv cs.AIresearchD-JEPA: Design-Recoverable JEPA Representation with Swappable Physics Decoders
arXiv:2609.33110v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) provide a framework for learning compact representations without directly reconstructing high-dimensional observations. H…
- arXiv cs.AIagentsParallelPilot: Supporting Coordination and Monitoring in Parallel AI Coding
arXiv:2609.33113v1 Announce Type: cross Abstract: As coding assistants become increasingly autonomous, developers run multiple sessions in parallel, shifting the challenge from code generation alone to coordinating and m…
- arXiv cs.AIagentsECG-Scroll: A Long-Horizon, Streaming Benchmark and Agent Environment for Interpretation of Ambulatory Electrocardiograms
arXiv:2609.33117v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) can now interpret a standard ten-second, twelve-lead electrocardiogram (ECG) with clinically grounded, reward-verified reasoning.…
- arXiv cs.AIresearchMedRouter: Demystifying Knowledge Differences Across Medical LLMs for Routing-Based Reasoning
arXiv:2609.33119v1 Announce Type: cross Abstract: Medical question answering spans diverse specialties and modalities, and individual medical large language models (LLMs) exhibit distinct strengths across tasks and domai…
- arXiv cs.AIresearchPolicy Plasticity Matters in Offline-to-Online Reinforcement Learning: Refitting Offline Policies for Online Adaptation
arXiv:2609.33127v1 Announce Type: cross Abstract: Offline-to-Online Reinforcement Learning (O2O RL) has emerged as a practical paradigm that pre-trains the policy using static offline datasets and subsequently adapts the…
- arXiv cs.AIresearchFlow-Matching-Based Protein Structure Tokenizer Made Efficient and Easy
arXiv:2609.33129v1 Announce Type: cross Abstract: As the bridge between protein modality and discrete modeling, protein structure tokenization still largely relies on heavily engineered training objectives tailored to sp…
- arXiv cs.AIresearchQuantum Monte Carlo Tree Search with Fixed Confidence
arXiv:2609.33132v1 Announce Type: cross Abstract: Recent advances in quantum computing are opening new opportunities for computationally intensive decision problems. This paper studies how quantum computing can improve M…
- arXiv cs.AIresearchBeyond the Training Horizon: Mechanisms and Limits of Length Generalization in Looped Transformers
arXiv:2609.33144v1 Announce Type: cross Abstract: Looped Transformers can generalize to reasoning chains longer than those encountered during training, but the computations enabling this behavior and limiting its extent…
- arXiv cs.AIagentsWhat Does a Skill Actually Do? Estimands and Evaluation Validity for Tool and Skill Use in LLM Agents: A Critical Review
arXiv:2609.33153v2 Announce Type: replace-cross Abstract: Reported improvements from tools and reusable skills in large language model agents refer to different comparisons. This critical narrative review examines what t…
- arXiv cs.AIresearchFOCUS: Benchmarking Retinal Model Generalization from Foundation Vision Encoders to Multimodal LLMs
arXiv:2609.33158v2 Announce Type: replace-cross Abstract: Progress in AI-based retinal image analysis has accelerated with the adoption of foundation models, yet evaluating their real-world reliability remains challengin…
- arXiv cs.AIagentsBeyond Tasks: A Vision for Reproducing an Animal-like Behavioral Substrate Using Modern Robot Learning Techniques
arXiv:2609.33165v1 Announce Type: cross Abstract: Recent advances in robot learning have produced increasingly capable embodied agents. Yet comparatively less attention has been given to a more basic form of competence t…
- arXiv cs.AIresearchDynamic Manipulation with World-Action Models via Counterfactual Planning
arXiv:2609.33172v1 Announce Type: cross Abstract: World-Action models (WAMs) trained on static demonstrations often fail to manipulate moving targets even when they possess the required manipulation skills. We attribute…
- arXiv cs.AIresearchScoring the Wrong Question: Readout Failures in Constrained-Option Evaluation
arXiv:2609.33179v1 Announce Type: cross Abstract: Constrained-option scoring reads a model's probabilities for a fixed set of permitted answers, so it returns a score even when the model is about to write something else.…
- arXiv cs.AIagentsWhich Self-Improvements Should We Trust? Reliable Self-Improvement When Agents Reuse Their Benchmarks
arXiv:2609.33180v2 Announce Type: replace-cross Abstract: As recursive self-improvement (RSI) rapidly advances, reliable evaluation becomes critical for guiding adaptive search. RSI typically relies on finite evaluation…
- arXiv cs.AIagentsTAO-DA: Towards Autonomous Operation--A Dual-Arm Vision-Language-Action Model for Coordinated Manipulation
arXiv:2609.33197v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models provide a unified framework for grounding high-level semantic information into low-level robot actions, enabling scalable robotic mani…
- arXiv cs.AIresearchSMORE: Stability-Promoting Mesh-Agnostic Model Reduction for Time-Dependent PDEs
arXiv:2609.33205v1 Announce Type: cross Abstract: High-fidelity simulations of time-dependent partial differential equations (PDEs) are computationally expensive, motivating data-driven reduced-order surrogates for many-…
- arXiv cs.AIresearchBeyond Calibration: Do a Typed-Decision Model's Probabilities Obey the Probability Axioms?
arXiv:2609.33209v1 Announce Type: cross Abstract: Typed-decision models such as TypeSafe's Jev answer a declared yes/no or multiple-choice question about a state with a probability instead of text, and their evaluations…
- arXiv cs.AIresearchScope-WM: Scoped Computation for Efficient Visual World Models
arXiv:2609.33218v1 Announce Type: cross Abstract: Visual world models enable robotic planning by predicting future observations, but dense latent-state propagation and sample-intensive trajectory optimization incur high…
- arXiv cs.AIresearchWhen Do Models Admit They Are Wrong? Failure Disclosure Is Unstable Under Reinforcement Learning
arXiv:2609.33220v1 Announce Type: cross Abstract: Outcome-based reinforcement learning can produce models with similar task performance but very different ways of communicating about their mistakes. We study failure disc…
- arXiv cs.AIagentsInspire: Benchmarking Scientific Literature Search for Open Research Problems
arXiv:2609.33233v1 Announce Type: cross Abstract: Scientific literature search often begins with an open research problem rather than a known target paper or a fixed candidate set. We introduce INSPIRE, a benchmark for e…
- arXiv cs.AIresearchVGGT-Diff: Visual Geometry Meets Diffusion for Sparse-View Novel View Synthesis
arXiv:2609.33253v2 Announce Type: replace-cross Abstract: We present VGGT-Diff, a geometry-routed multi-view diffusion model for sparse-view novel view synthesis. Existing novel view synthesis (NVS) methods face a fundam…
- arXiv cs.AIresearchBERT4DTI : BERT-based Model for Predicting Drug-Protein Interactions
arXiv:2609.33254v1 Announce Type: cross Abstract: Understanding how drugs interact with protein targets is fundamental to drug discovery, drug repurposing and the early identification of promising therapeutic candidates…
- arXiv cs.AIagentsVehDyn: A Driving World Model Benchmark for Vehicle Dynamics
arXiv:2609.33264v1 Announce Type: cross Abstract: Video world models are emerging as data engines, action planners, and generative simulators for autonomous driving, but existing benchmarks primarily assess visual fideli…
- arXiv cs.AIresearchSCISSOR: Score-Conditioned Instrument Source Separation for Orchestral Recordings
arXiv:2609.33265v1 Announce Type: cross Abstract: Orchestral separation recovers instrument sections from mixtures in which shared pitches, harmonics, and timbres obscure source identity. An aligned score provides instru…
- arXiv cs.AIresearchDomain Generalization under Sampling Pattern Shifts in Irregular Time Series
arXiv:2609.33279v1 Announce Type: cross Abstract: Irregularly sampled multivariate time series (ISMTS) are prevalent in real-world applications, where both observation times and available measurements can vary substantia…
- arXiv cs.AIagentsAquaWAM: A Dynamics-aware World Action Model for Underwater Embodied Agents
arXiv:2609.33299v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) are becoming increasingly important and useful for embodied intelligence, as they enable robots to anticipate the consequences of candi…
- arXiv cs.AIresearchHesitation-Aware On-Policy Distillation for Diffusion Language Models
arXiv:2609.33301v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iterative unmasking. At each denoising step, a dLLM proposes a token at every masked position, but the decoder co…
- arXiv cs.AIresearchBITS: Rethinking Fair and Comprehensive Evaluation for Irregular Time Series Forecasting
arXiv:2609.33303v1 Announce Type: cross Abstract: Despite recent progress in irregular time series forecasting, the field still lacks a unified benchmark for fair and comprehensive evaluation. Existing evaluations are of…
- arXiv cs.AIresearchZeroGAR: Benchmarking the Adversarial Robustness of Zero-Shot Graph Models
arXiv:2609.33314v1 Announce Type: cross Abstract: Zero-shot graph models (ZGMs), which learn transferable knowledge from source graphs and directly apply to unseen target graphs without any adaptation, have achieved prom…
- arXiv cs.AIagentsRobust Hierarchical Structures for Agentic Document Analysis
arXiv:2609.33322v1 Announce Type: cross Abstract: Large Language Models (LLMs) enable us to better understand text documents, including PDFs and Word documents. However, LLMs, as well as more modern LLM agents, i.e., tho…
- arXiv cs.AIagentsDoes Learning to Predict the World Help Agents Act? Auditing World-Model Post-Training
arXiv:2609.33335v1 Announce Type: cross Abstract: Predicting how an environment will change before acting is a natural route to better decision making for agents. Recent post-training methods therefore require agents to…
- arXiv cs.AIresearchBeyond Conservatism: Recoverability-Conditioned Exploration for Model-Based Imitation Learning
arXiv:2609.33336v1 Announce Type: cross Abstract: Model-based imitation learning (MBIL) improves real-environment interaction efficiency by optimizing policies on imagined rollouts from a learned world model. However, th…
- arXiv cs.AIresearchCHI: A Composite Hallucination Index Unifying Entity, Relation, and Quantity Dimensions for Summarization Evaluation
arXiv:2609.33343v1 Announce Type: cross Abstract: Faithfulness evaluation of abstractive summaries remains an open challenge, with existing metrics addressing only isolated hallucination types: factual entity errors, rel…
- arXiv cs.AIresearchKoopCell: Koopman-Based Generative Model for Learning Single-Cell Dynamics from Distribution Snapshots
arXiv:2609.33350v1 Announce Type: cross Abstract: Learning population dynamics from temporally sparse, unpaired distribution snapshots is a fundamental challenge in developmental biology. Recent approaches based on neura…
- arXiv cs.AIagentsAPI Secrets Should Never Become Tokens in the LLM's Vocabulary: A Threat Analysis of API Credential Handling in LLM Agent Systems and an Empirical Evaluation of a Vault-Mediated Execution Boundary
arXiv:2609.33371v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents turn credential hygiene from a storage problem into an execution-security problem. A key pasted into a prompt, or embedded in…
- arXiv cs.AIresearchWhat Survives the Codec Shift: Pooled No-Vocals Residuals for Speech Deepfake Detection
arXiv:2609.33375v1 Announce Type: cross Abstract: The transition from vocoder-based to neural-codec speech synthesis makes generalization more difficult for speech deepfake detectors, particularly those relying on speech…
- arXiv cs.AIagentsRecursive Harness Distillation across Agents for Robot Manipulation
arXiv:2609.33378v1 Announce Type: cross Abstract: A central goal in robotics is to enable manipulation across changing tasks and environments. Vision-language-action (VLA) models provide broad manipulation capabilities b…
- arXiv cs.AIagentsNLPG: Natural-Language Policy Gradients for Self-Evolving Language Agents
arXiv:2609.33379v1 Announce Type: cross Abstract: Large language model agents increasingly rely on compound programs for retrieval, tool use, reasoning, and verification, yet their failures often arise from local procedu…
- arXiv cs.AIresearchFrom Position Risks to Block Survival: Faster Generation for Diffusion Language Models
arXiv:2609.33390v1 Announce Type: cross Abstract: Diffusion language models (DLMs) can accelerate generation by predicting multiple tokens in parallel, but there is a mismatch between how these tokens are predicted and h…
- arXiv cs.AIagentsBeyond Timestamps: Decision-Aligned On-Policy Distillation for Long-Horizon Agents
arXiv:2609.33391v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) often relies on sparse outcome rewards, providing coarse supervision for long-horizon agents. On-policy self-distill…
- arXiv cs.AIresearchAutoHGNN: Robust and Efficient Neural Architecture Search for Hypergraph Neural Networks
arXiv:2609.33392v1 Announce Type: cross Abstract: Hypergraph neural networks have achieved significant success in recent years. However, manual architecture crafting is labor-intensive and often fails to capture complex,…
- arXiv cs.AIagentsEvaluating System One Models for Agent Security Decisions: Reliability, Calibration, and Selective Automation
arXiv:2609.33401v3 Announce Type: replace-cross Abstract: Agentic software connects language models to tools that modify files and interact with external services. Developers use model-based security checks to screen ext…
- arXiv cs.AIagentsDataMagic: Authoring Data Videos through Declarative Multi-Agent Orchestration
arXiv:2609.33403v1 Announce Type: cross Abstract: Data videos communicate data insights through dynamic charts, voice narration, and synchronized animations, and have become a widely adopted form of data storytelling. Ho…