AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchHow Causality Bridges the Semantic Gap
arXiv:2610.02594v1 Announce Type: cross Abstract: Numerical measurements capture how a system behaves, but often leave the meanings of its variables unspecified. Some variables are measured but never labeled, and others…
- arXiv cs.AIagentsWebUIProof: Benchmarking WebUI Code Generators with UI-Agent Execution Harness
arXiv:2610.02617v1 Announce Type: cross Abstract: Evaluating WebUI code generation at scale is difficult: outputs may compile and look plausible yet fail under user interaction, and prior benchmarks largely rely on free-…
- arXiv cs.AIresearchEquivariant Flow Matching for Electron Density Prediction
arXiv:2610.02651v1 Announce Type: cross Abstract: Machine learning surrogates for density functional theory (DFT) have been increasingly used to reduce the cost of first-principles calculations. In this arena, predicting…
- arXiv cs.AIresearchDistributed Learning with Selective State Space Models: Architecture-Aware Convergence Analysis
arXiv:2610.02659v2 Announce Type: replace-cross Abstract: Modern state space models (SSMs), such as Mamba2, provide a compelling alternative to transformers by combining linear-time sequence modeling with recurrent state…
- arXiv cs.AIresearchGeneralization Bounds for Flow-matching Generative Models for Intrinsically Low-dimensional Data
arXiv:2610.02663v2 Announce Type: replace-cross Abstract: Despite the remarkable empirical success of flow-matching models, their statistical generalization guarantees remain underdeveloped. Existing analyses often impos…
- arXiv cs.AIresearchLarge Language Continuous Diffusion Models
arXiv:2610.02665v1 Announce Type: cross Abstract: Despite the success of discrete diffusion language models (dLMs) for fast parallel decoding, their non-smooth, high-dimensional space hinders trajectory steering for reas…
- arXiv cs.AIagentsLEAP: Learning Efficient Action Proposals For LLM Agents
arXiv:2610.02670v1 Announce Type: cross Abstract: LLM agents are known to be slow in rollouts. An agent completes a task one step at a time. At each step, it reasons and then chooses an action to execute. The next step a…
- arXiv cs.AIresearchTest-time Calibration Learning for Large Language Model Reasoning
arXiv:2610.02695v1 Announce Type: cross Abstract: Reliable large language models (LLMs) must not only produce accurate answers but also express confidence that faithfully reflects their probability of being correct. Such…
- arXiv cs.AIresearchMuonIO: Principled Norm-Aware Descent for Embedding Tables and Language Model Heads
arXiv:2610.02705v1 Announce Type: cross Abstract: The Muon optimizer derives its update rule for hidden linear layers by solving a local linearization of the loss penalized by the spectral norm, motivated by an RMS-stabi…
- arXiv cs.AIagentsSelf-Supervised Scaling of Terminal Environments for Scientific Domains
arXiv:2610.02710v1 Announce Type: cross Abstract: Terminal agents are increasingly deployed beyond software engineering in science and other specialized domains. Constructing training environments requires executable ref…
- arXiv cs.AIresearchRevisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis
arXiv:2610.02718v1 Announce Type: cross Abstract: Vision-language models such as CLIP exhibit strong semantic generalization, but remain limited in fine-grained visual perception. A recent work named KUEA presents a natu…
- arXiv cs.AIresearchTPBench: A Turning-Point Benchmark for Dialogue Compression
arXiv:2610.02736v1 Announce Type: cross Abstract: A compressor can keep the facts of a dialogue and still drop the turn that changed them. A user corrects a price, reverses a choice, or adds a constraint. We call this fa…
- arXiv cs.AIagentsProspective Hindsight: Self-Calibrating Reinforcement Learning via Prediction-Reality Gaps
arXiv:2610.02740v1 Announce Type: cross Abstract: Reinforcement learning for long-horizon agents relies on purely retrospective training signals: credit is assigned only after observing environmental consequences, leavin…
- arXiv cs.AIresearchCorrecting Guided Diffusion Trajectories with Spectral Alignment
arXiv:2610.02753v1 Announce Type: cross Abstract: The practical success of conditional image generation hinges on fine-grained differences in condition alignment and visual fidelity. Classifier-free guidance (CFG) is cen…
- arXiv cs.AIagentsWhen History Fails to Become Experience: Action Calibration in Language Agents
arXiv:2610.02769v1 Announce Type: cross Abstract: Language agents should draw on prior attempts and environmental feedback to improve subsequent decisions within the same task. However, providing additional interaction h…
- arXiv cs.AIresearchNearly Optimal Fixed-Confidence Best-Arm Identification with 1-Bit Feedback
arXiv:2610.02771v1 Announce Type: cross Abstract: We study fixed-confidence best-arm identification under strict 1-bit feedback constraints. At each round, the learner selects an arm and a query set, and receives only a…
- arXiv cs.AIresearchImproving Atomic-Fact Recall via Focused Views in Unstructured Knowledge Editing
arXiv:2610.02772v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly serve as general-purpose interfaces to factual knowledge, but their parameters do not automatically reflect information that cha…
- arXiv cs.AIresearchOPD Before RL: Warm-Starting Rubric-Based RL with On-Policy Distillation
arXiv:2610.02781v1 Announce Type: cross Abstract: Many useful language-model tasks cannot be evaluated by exact outcome verification. Rubric-based reinforcement learning (RL) addresses this issue by scoring open-ended re…
- arXiv cs.AIresearchAdaptive Spectral-Koopman Dynamics Modeling for Temporal Domain Generalization
arXiv:2610.02822v1 Announce Type: cross Abstract: Temporal Domain Generalization (TDG) has emerged to address real-world streaming data with distribution shifts over time. However, existing methods are either prone to ov…
- arXiv cs.AIresearchFastOPD: On-Policy Distillation for Lightweight VLA Deployment
arXiv:2610.02832v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) foundation models have scaled rapidly to enhance manipulation performance and generalizability, but this scaling incurs high computational co…
- arXiv cs.AIresearchDistributionally Robust Survival Models under Subpopulation Shift and Outlier Contamination
arXiv:2610.02868v1 Announce Type: cross Abstract: Learning robust survival models under distribution shift is an important but challenging problem in many applications. In heterogeneous populations, a model that performs…
- arXiv cs.AIagentsAgentTrap: Stateful Feedback Deception against Autonomous Penetration Testing Agents
arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common defense, honeypots can…
- arXiv cs.AIresearchConvoDrift: A Multi-Turn Conversational Dataset for Modeling Stylistic Tone Evolution
arXiv:2610.02873v1 Announce Type: cross Abstract: The evolution of linguistic style in conversations is an underexplored issue in NLP. Most style-control datasets focus on sentences or assume a static style throughout, m…
- arXiv cs.AIresearchQuery-aware routing for Cross-lingual performance gains in Encoders
arXiv:2610.02875v1 Announce Type: cross Abstract: Multilingual encoders can exhibit reduced retrieval effectiveness when queries and relevant documents differ in language, despite strong same-language performance. We inv…
- arXiv cs.AIresearchDyRA: Dynamic Residual Approximation for Efficient Matrix Multiplication in DNNs
arXiv:2610.02882v1 Announce Type: cross Abstract: Large-scale foundation models achieve strong performance across diverse tasks, but their size makes inference costly, largely due to dense matrix multiplications. Prior w…
- arXiv cs.AIresearchMisinformation Without Triggers: From Factual Answers to Downstream Decisions
arXiv:2610.02886v1 Announce Type: cross Abstract: Language models learn from web documents, some of them false, and false content can reach a model's answer to a factual question and the summaries and decisions that use…
- arXiv cs.AIresearchRevealing Epistemic Uncertainty in MLLMs via Causal-Invariant Masking
arXiv:2610.02887v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) suffer from hallucinations, creating a critical need for Uncertainty Quantification (UQ) to ensure reliable deployment. However,…
- arXiv cs.AIresearchWhen Can We Trust the Matching Principle? Robust Deployment Geometry Under Finite-Sample and Model Uncertainty
arXiv:2610.02894v1 Announce Type: cross Abstract: Match only geometry you can identify; otherwise spread the penalty. We quantify that decision by the trust ratio tau = epsilon / gamma (estimation uncertainty over spectr…
- arXiv cs.AIagentsDiscriminating Fixture Coverage in Agent-Infrastructure Verification Suites
arXiv:2610.02928v1 Announce Type: cross Abstract: Invariant suites and runtime monitors increasingly gate agent deployment decisions, and the evidence offered for any particular suite is almost always a single observatio…
- arXiv cs.AIagentsDynamic Expert Pruning for Multi-Agent Systems
arXiv:2610.02951v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures scale language models efficiently by activating only a few experts per token, but the saving is confined to computation: every expe…
- arXiv cs.AIresearchPost-Training Frontier Text-to-Image Models by Composing Preference and Rubric Rewards
arXiv:2610.02967v2 Announce Type: replace-cross Abstract: Recent text-to-image generation models have achieved remarkable visual quality, but improving them through post-training remains challenging because no single rew…
- arXiv cs.AIagentsSentry: Learning to Recover from LLM Agent Failures at Test Time
arXiv:2610.02994v1 Announce Type: cross Abstract: LLM agents often fail mid-task due to invalid tool calls, repeated actions, or poorly grounded reasoning, and learning from these failures is a path to reliability. We fi…
- arXiv cs.AIresearchTemporal Geometry of Deep Networks: Hyperbolic Representations of Training Dynamics for Intrinsic Explainability
arXiv:2610.03000v1 Announce Type: cross Abstract: Intrinsic explainability remains a challenging problem, particularly in contexts where multilayer perceptrons (MLPs) require dynamic re-training within an optimization en…
- arXiv cs.AIresearchAvoKV-E: Payload-Aware KV Cache Eviction for Long Reasoning
arXiv:2610.03007v1 Announce Type: cross Abstract: Long-output reasoning shifts the KV-cache bottleneck from the fixed prompt to the generated trace. Existing reasoning-cache eviction methods largely treat cached entries…
- arXiv cs.AIagentsBeyond Predefined Sinks: Security-Aware Dependency Analysis for LLM Agents
arXiv:2610.03014v1 Announce Type: cross Abstract: Large language model (LLM)-based agents increasingly connect model-generated decisions to security-sensitive software capabilities such as command execution, filesystem a…
- arXiv cs.AIagentsOmniAct3D: Leveraging Foundation Geometry and Evidence-Grounded Reasoning for Panoramic 3D Detection
arXiv:2610.03015v1 Announce Type: cross Abstract: Accurate 3D detection is essential for mobile embodied agents, while Vision Foundation Models (VFMs) offer transferable visual and geometric priors. Yet existing VFM-base…
- arXiv cs.AIresearchTailoring the Quantization Space for 1-Bit KV Cache Compression
arXiv:2610.03027v1 Announce Type: cross Abstract: The key-value (KV) cache becomes a major memory bottleneck in long-context LLM inference, placing substantial pressure on memory capacity and bandwidth. To mitigate this…
- arXiv cs.AIagentsWebFovea: When the Model Is Right but the Click Is Wrong -- Reliable Round Trips for Vision-Based Web Agents on Live Websites
arXiv:2610.03036v2 Announce Type: replace-cross Abstract: We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100. The challenge evaluates ag…
- arXiv cs.AIresearchNegT2IBench: When Negation Changes the Picture. A Polarity Benchmark for Text-to-Image Models
arXiv:2610.03084v1 Announce Type: cross Abstract: Text-to-image (T2I) models are judged by benchmarks that measure whether requested content appears, but these benchmarks largely overlook the complementary ability to sat…
- arXiv cs.AIresearchZephon: Elastic Determinism for Online, Stateful Foundation Model Data Loading Pipelines
arXiv:2610.03087v1 Announce Type: cross Abstract: Deterministic data loading is important for foundation model development: model researchers need confidence that differences they observe across costly ablations are caus…
- arXiv cs.AIagentsSecuring Computer-Use Agents Against Branch Steering Attacks
arXiv:2610.03089v1 Announce Type: cross Abstract: Modern Computer Use Agents (CUAs) directly interact with graphical user interfaces and execute third-party web tools, exposing them to indirect prompt injection across ev…
- arXiv cs.AIresearchULTRADISCOVERY: Abductive Exploration in an Interconnected, Epistemically Open Universe
arXiv:2610.03092v3 Announce Type: replace-cross Abstract: Scientific discovery often begins when scattered clues call for a new way of describing the world. Such abductive exploration can require constructing the represe…
- arXiv cs.AIresearchBeyond Single Videos: Benchmarking and Active Evidence Seeking for E-Commerce Cross-Video Reasoning
arXiv:2610.03099v1 Announce Type: cross Abstract: E-commerce videos are information-dense and frequently compared by consumers evaluating products and merchants assessing marketing strategies. However, existing multimoda…
- arXiv cs.AIagentsAsk, Relax, or Act? Evaluating Actionable Indeterminacy in LLM Preference Reasoning
arXiv:2610.03102v1 Announce Type: cross Abstract: An LLM agent can recognize uncertainty yet still choose the wrong next step: asking when action is already justified, or seeking clarification when the constraints must c…
- arXiv cs.AIresearchS2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales
arXiv:2610.03106v1 Announce Type: cross Abstract: The subseasonal-to-seasonal (S2S) timescale, roughly from two weeks to two months ahead, is a critical forecast window for sectors such as agriculture, energy, and water…
- arXiv cs.AIresearchHow to Find and Reuse Policies for Continuous Adaptation in Lifelong Reinforcement Learning
arXiv:2610.03119v1 Announce Type: cross Abstract: In lifelong reinforcement learning, retaining previously learned policies is not sufficient for effective transfer to a new task. Useful knowledge may be distributed acro…
- arXiv cs.AIresearchForesight: planning future perception in streaming VLMs without retraining
arXiv:2610.03123v1 Announce Type: cross Abstract: Existing streaming vision-language models (VLMs) continuously perceive and reason over visual streams, but their computational pathways remain fixed throughout inference.…
- arXiv cs.AIresearchThe Fragility of Trigger-Tag Mechanisms for Misuse Detection in Open-Weight LLMs
arXiv:2610.03124v1 Announce Type: cross Abstract: Open-weight language models can be downloaded, modified, and deployed beyond their developers' control, limiting the effectiveness of centrally enforced safeguards. Recen…
- arXiv cs.AIagentsEvoRiskBench: An Evolving Benchmark for Runtime Security Risks in Workspace Agents
arXiv:2610.03153v1 Announce Type: cross Abstract: Workspace agents combine large language models with execution harnesses to perform stateful, multi-step tasks that access or modify external resources. Existing benchmark…
- arXiv cs.AIresearchMultimodal reasoning for broadly neutralizing antibody discovery from label-free human B cell repertoires across virus families
arXiv:2610.03160v1 Announce Type: cross Abstract: Discovering broadly neutralizing antibodies (bnAbs) from human natural immune repertoires remains a fundamental challenge in immunology, hindered by: the extreme rarity o…