AI news archive.
19,854 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchIdentically Trained Language Models Break on Different Jailbreaks
arXiv:2610.34074v1 Announce Type: cross Abstract: Jailbreak benchmarks test one checkpoint and treat which jailbreaks break it as a property of its pretraining data and safety training. We ask whether another pretraining…
- arXiv cs.AIresearchT2D: Target-to-Draft Model Pruning & Adaptation for Efficient Speculative Decoding
arXiv:2610.34103v1 Announce Type: cross Abstract: Speculative decoding significantly accelerates autoregressive text generation in Large Language Models (LLMs), but its efficacy depends largely on two key factors: the di…
- arXiv cs.AIresearchHumanoidNDM: Closing the Training-Deployment Gap of Motion Tracking via Humanoid Neural Dynamics Model
arXiv:2610.34126v1 Announce Type: cross Abstract: Humanoid robots have recently achieved remarkable success in motion tracking. However, during real-world deployment, robots inevitably encounter dynamics gaps arising fro…
- arXiv cs.AIresearchDecoupled Prune-and-Reconstruct: Training on a Compact Core with Double-Layer Sparsification
arXiv:2610.34140v1 Announce Type: cross Abstract: On million-node graphs, the memory wall arrives before the compute wall: a GNN that never fits in VRAM cannot deliver the all-node inference its accuracy promises. The st…
- arXiv cs.AIresearchRethinking Retrieval in the Long-Context Era: Training-Free Semantic Trees for Adaptive Context Construction
arXiv:2610.34146v1 Announce Type: cross Abstract: Long-context language models can increasingly process entire documents, making full-context prompting a practical alternative to passage retrieval. However, greater capac…
- arXiv cs.AIresearchSingle-Cycle Battery Remaining Useful Life Prediction with Compressed Continuous Wavelet Features and Deep Neural Networks
arXiv:2610.34159v1 Announce Type: cross Abstract: Lithium-ion batteries are widely used in industrial applications, but their performance gradually degrades over time, making accurate lifetime prediction important for sa…
- arXiv cs.AIresearchWrite What Matters: Disentangling Token Selection from Slot Allocation in Recurrent Memory
arXiv:2610.34180v1 Announce Type: cross Abstract: Long-sequence models must retain earlier information. Full attention keeps all past tokens but grows expensive, and recurrent-memory models compress history into fixed sl…
- arXiv cs.AIresearchEntropic Control for Homeostatic Optimization: Pre-empting Catastrophic Forgetting via Dynamic Feedback
arXiv:2610.34182v1 Announce Type: cross Abstract: Supervised Fine-Tuning (SFT) of LLMs suffers from catastrophic forgetting, and prevailing mitigation strategies struggle to reconcile the plasticity-stability dilemma. To…
- arXiv cs.AIresearchSRA: Selective Residual Adaptation for LLM Reasoning Enhancement
arXiv:2610.34199v1 Announce Type: cross Abstract: Knowledge distillation transfers reasoning capabilities from large language models to lightweight students. However, distilled small models still struggle with multi-step…
- arXiv cs.AIresearchCORMA: Constraint-Routed Decision Mamba for Generalizable Multi-Constraint Offline Safe Reinforcement Learning
arXiv:2610.34208v1 Announce Type: cross Abstract: Offline safe reinforcement learning (RL) learns safety-aware policies from static datasets while satisfying safety constraints during deployment. Motivated by the strong…
- arXiv cs.AIresearchStaX-Net: Stackelberg Interleaved Asymmetric Network for Cross-Modality Medical Image Translation
arXiv:2610.34214v1 Announce Type: cross Abstract: Cross-modality medical image translation is challenged by anatomically inconsistent synthesis that can compromise clinical diagnosis. We propose StaX-Net, a Stackelberg i…
- arXiv cs.AIagents$\Delta\tau$-Bench: Pushing Agents Toward a Moving Capability
arXiv:2610.34238v1 Announce Type: cross Abstract: In this paper, we introduce $\Delta\tau$-Bench, an executable agent benchmark that models the structural evolution of large tool ecosystems. In $\Delta\tau$-Bench, indepe…
- arXiv cs.AIagentsNameTrap: Steering AI Coding Agents Toward Security Vulnerabilities via Variable Names
arXiv:2610.34253v1 Announce Type: cross Abstract: AI coding agents routinely clone repositories, install packages, and read source code obtained from the Web, so publicly hosted code becomes part of the context that shap…
- arXiv cs.AIresearchRecovering Business Rules as Cascade Lookups for Enterprise Field Prediction
arXiv:2610.34258v1 Announce Type: cross Abstract: Enterprise sales-order systems rely on manually maintained configuration rules to determine fields such as payment terms, shipping points, and sales ownership. When these…
- arXiv cs.AIresearchDoubleFree:Exploiting Exploration History for Rollout-Free Multi-Task LLMs Training
arXiv:2610.34272v1 Announce Type: cross Abstract: Multi-task post-training can develop domain specialists through independent reinforcement learning (RL) and consolidate their capabilities through multi-teacher on-policy…
- arXiv cs.AIresearchRepairing Broken Access Control in Web Applications with LLMs: An Empirical Benchmark Study
arXiv:2610.34290v1 Announce Type: cross Abstract: Broken access control (BAC) ranks among the most severe web-application vulnerability classes, yet its automated repair remains largely unexplored. Unlike memory-safety v…
- arXiv cs.AIresearchAutomated, auditable dating of the Babylonian Astronomical Diaries with language models and astronomical tools
arXiv:2610.34297v1 Announce Type: cross Abstract: The Babylonian Astronomical Diaries record the sky over nearly six centuries. Many tablets are broken and have lost their date formula. Experts dated many of them one tab…
- arXiv cs.AIresearchDeveloper Task Delegation to LLMs and the Trust Factor: A Mixed Methods Study
arXiv:2610.34317v1 Announce Type: cross Abstract: With the rise of Large Language Models (LLMs), software developers are presented with a powerful new approach: delegating software development tasks to LLMs. Existing stu…
- arXiv cs.AIresearchSHIFT-JEV: Certified Abstention and Gain-Gated Continual Adaptation for LLM-Based Decision Models under Distribution Shift
arXiv:2610.34329v1 Announce Type: cross Abstract: Large language models (LLMs) can act as decision models that return a probability distribution over a fixed set of options, but deployed decision models face domain, labe…
- arXiv cs.AIresearchCoLink: Global Compression and Knowledge Linking for Multi-Turn Dialogue Modeling
arXiv:2610.34335v1 Announce Type: cross Abstract: Extracting salient information from long-horizon dialogue histories remains a significant challenge for Large Language Models (LLMs) due to the restricted context windows…
- arXiv cs.AIresearchImproving the Chain-of-Thought Compressibility of Pruned Reasoning Models via Long--Short Contrastive Pruning
arXiv:2610.34336v1 Announce Type: cross Abstract: Large reasoning models are costly to serve because they are large and because they generate long chains of thought (CoT). Weight pruning and CoT compression address these…
- arXiv cs.AIresearchXing USP: A Cross-Family Semantic Contract for Information Extraction and Intent-Slot Parsing
arXiv:2610.34343v1 Announce Type: cross Abstract: Structured semantic parsing is typically judged by whether the correct category is assigned, which leaves value recovery and instance-level associations unexamined: a sys…
- arXiv cs.AIagentsSEEK: Skill Extraction with Evolving Knowledge against Frontier Science Agents
arXiv:2610.34365v2 Announce Type: replace-cross Abstract: Science agents increasingly package domain expertise as reusable skills that plan analyses, select tools, and execute workflows. This modularity creates a confide…
- arXiv cs.AIresearchComBeautify: Leveraging Code Change Summaries for Conventional Commit Generation
arXiv:2610.34374v1 Announce Type: cross Abstract: Modern software development relies on version control systems such as Git to track changes and facilitate collaboration. While commit messages are crucial for conveying d…
- arXiv cs.AIresearchWhether or Where? Tail Calibration Signals Finite-Budget Reward Hacking in Best-of-N Selection
arXiv:2610.34375v1 Announce Type: cross Abstract: Best-of-N (BoN) inference returns the candidate with the highest proxy reward, so a larger $N$ tests the proxy's extreme tail more than its average ranking quality. We sh…
- arXiv cs.AIagentsAndroidFlux: Evaluating and Reward Modeling Failure Recovery Capabilities in Mobile Use Multimodal Agents
arXiv:2610.34384v1 Announce Type: cross Abstract: Mobile-use multimodal agents are typically evaluated by task success from a clean initial state, which does not isolate their ability to recover from intermediate errors.…
- arXiv cs.AIagentsOutcome-Aware Agents: When Does Causal Structure Help a Forward Model Foresee the Consequences of Actions?
arXiv:2610.34385v1 Announce Type: cross Abstract: Agents that act on real systems should predict what their actions will cause before acting. We study when causal structure helps a learned forward model do this, using a…
- arXiv cs.AIagentsParetoRSI-Gym: Can AI Agents Improve Language Models Across Multiple Domains?
arXiv:2610.34386v1 Announce Type: cross Abstract: Recursive self-improvement (RSI) requires an agentic system to design, train, and evaluate its own successor. Data-driven post-training is a central part of that loop, ye…
- arXiv cs.AIresearchDynamic Multi-Step Decoding for Time-Series Foundation Models
arXiv:2610.34409v1 Announce Type: cross Abstract: Time-series forecasting models typically use a fixed decoding strategy at inference time: either one-shot prediction of the full horizon or autoregressive rollout over at…
- arXiv cs.AIresearchIn-Context Adapter Generation for Compositional Generalization in Large Audio Language Models
arXiv:2610.34413v1 Announce Type: cross Abstract: Large audio language models (LALMs) have achieved strong performance on standard speech and audio understanding tasks, yet their ability to systematically generalize to n…
- arXiv cs.AIresearchSpatial Audio Generation and Editing with Executable Plans and Self-Distilling Transfusion
arXiv:2610.34415v1 Announce Type: cross Abstract: Spatial audio authoring coordinates source decisions with soundfield synthesis. For editing, plans specify what to change and retain, while reference audio supplies furth…
- arXiv cs.AIagentsMulFCoder: Framework-conditioned Multi-agent for MLLM-based Multi-framework Front-end Code Generation
arXiv:2610.34418v1 Announce Type: cross Abstract: Generating runnable front-end code from UI screenshots is a long-standing goal in automated software engineering. Existing MLLM-based methods predominantly focused on HTM…
- arXiv cs.AIagentsCyberDual: AI Attackers versus AI Code Reviewers in Real Software Maintenance
arXiv:2610.34435v1 Announce Type: cross Abstract: Open-source projects now let AI agents review incoming code, but the code under review may itself come from an AI attacker. We present CyberDual, an arena for this dual r…
- arXiv cs.AIagentsEvolveMAS: A Unified Self-Evolution Framework for Decentralized Multi-Agent Systems
arXiv:2610.34450v1 Announce Type: cross Abstract: Decentralized multi-agent systems (MAS) enable large language model agents to interact without centralized control. Agents need to adapt to other agents at test time and…
- arXiv cs.AIresearchEfficient Proof Generation for Lean Statements with Multiple Candidate Answers
arXiv:2610.34490v1 Announce Type: cross Abstract: In formal systems such as Lean 4, efficiently finding answers to mathematical problems and generating verifiable proofs is an important task in automated mathematical rea…
- arXiv cs.AIresearchCertifying Distributionally Robust Decisions from Projection Observations
arXiv:2610.34493v1 Announce Type: cross Abstract: A scalar measurement can determine a robust decision without identifying the latent covariance or every decision risk. We study finite Gaussian projection experiments wit…
- arXiv cs.AIresearchMultimodal Requirements Traceability Link Recovery in Industrial Settings
arXiv:2610.34503v1 Announce Type: cross Abstract: Requirements traceability links support activities such as change-impact analysis, coverage checking, and validation. Industrial requirements can include traceable images…
- arXiv cs.AIagentsThe Price of Scale in Proactive Memory Recall
arXiv:2610.34507v2 Announce Type: replace-cross Abstract: A long-lived assistant that brings up memories without being asked must decide at every turn whether anything in its store is worth an interruption. We show that…
- arXiv cs.AIresearchTRIAGE: Efficient Vision-Language-Action Inference Needs Both Reuse and Pruning
arXiv:2610.34519v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are increasingly used for robot manipulation because they map camera images and a language instruction directly to actions. Robots tha…
- arXiv cs.AIresearchConviction Without Evidence: Verdict Stability Is Independent of Visual Grounding in Medical Vision--Language Models
arXiv:2610.34520v1 Announce Type: cross Abstract: Vision--language models applied to medical question answering can reach correct diagnoses without using the diagnostic image, inferring instead from the clinical vignette…
- arXiv cs.AIresearchAcute Stroke Classification Using Asymmetric Data Standardization and Orthogonal-Focal Loss Optimized CNN-ViT Cross-Attention Fusion: A Multicenter External Validation Study
arXiv:2610.34529v1 Announce Type: cross Abstract: Background/Objectives: Rapid differentiation of ischemic and hemorrhagic stroke subtypes is vital for acute management. Although current deep learning models achieve high…
- arXiv cs.AIagentsSentryBench: A Cost-Sensitive Benchmark for Adversarial Robustness of Tool-Using LLM Agents in Public-Safety Deployments
arXiv:2610.34535v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly wired to consequential tools that send public alerts, dispatch responders, and query citizen records, where one erroneo…
- arXiv cs.AIagentsLLM WikiLeaks: Uncovering URL-Based Capability Extension and Security Circumvention in Agentic Message Boards
arXiv:2610.34542v1 Announce Type: cross Abstract: Autonomous agents have been observed acting beyond their assigned tasks, accessing unauthorized systems, and establishing communication channels to exchange information,…
- arXiv cs.AIresearchGRASP: Group-Adaptive Hybrid RL-SFT Post-Training for Medical VQA without Reasoning Annotations
arXiv:2610.34561v1 Announce Type: cross Abstract: Adapting general-purpose vision-language models (VLMs) to medical visual question answering (VQA) is valuable for helping clinicians read images and make diagnoses, but a…
- arXiv cs.AIresearchRecursive CLIP: Vision-Language Distillation with Looped Transformer Blocks
arXiv:2610.34563v1 Announce Type: cross Abstract: Contrastive vision-language models such as CLIP typically rely on independently parameterized transformer blocks across depth. We investigate the extent to which these bl…
- arXiv cs.AIresearchLarge Language Models: A Plain-Language Overview for Engineers
arXiv:2610.34585v1 Announce Type: cross Abstract: Large language models (LLMs) are neural networks trained on huge text collections to generate text by predicting what comes next. Engineers using ChatGPT and other genera…
- arXiv cs.AIresearchHARP-LoRA: Hierarchy-Conditioned Rank Projection for Low-Rank Adaptation in Scientific Table Understanding
arXiv:2610.34589v1 Announce Type: cross Abstract: Tabular data is widely used in scientific applications, where complex layouts, including multi-level headers, merged cells, captions, and footnotes, make information extr…
- arXiv cs.AIresearchAudio-R1: Audio Reasoning through Reinforcement Learning on Self-Supervised Tasks
arXiv:2610.34609v1 Announce Type: cross Abstract: Reasoning is increasingly important for large audio-language models (LALMs), yet remains relatively underexplored compared with text-only and vision-language models. We i…
- arXiv cs.AIresearchEntity Matching using Decision Models
arXiv:2610.34626v1 Announce Type: cross Abstract: Entity matching is the task of deciding whether two records describe the same real-world entity. Current entity matching methods rely on pre-trained language models (PLMs…
- arXiv cs.AIresearchRIDE-Splat: Reflection Removal for In-the-Wild Driving Environments
arXiv:2610.34632v1 Announce Type: cross Abstract: Driving video captured through a windshield violates the world-space consistency assumed by 3D Gaussian Splatting (3DGS): the road scene exhibits parallax while cabin ref…