AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsAI Agent Pull Requests on GitHub: Frequency, Structure, and Merge Conflict Rates
arXiv:2607.04697v2 Announce Type: cross Abstract: AI coding agents may generate and submit Pull Requests (PRs) to the same repository at the same time. However, research concerning the extent of concurrent submission by…
- arXiv cs.AIagentsUsing Process Mining to Generate AI Agents from Software Engineering Process Records
arXiv:2607.04948v1 Announce Type: cross Abstract: Integrating AI agents into Software Engineering (SE) raises an important challenge: how can we specify and realize AI agents that work effectively alongside humans in hyb…
- arXiv cs.AIresearchBeyond Private Training: The New Landscape of AI Privacy
arXiv:2609.19456v1 Announce Type: cross Abstract: Retrieval-augmented systems increasingly rely on vector indexes that may retain deleted items in their search graph. Existing deletion interfaces can prevent deleted iden…
- arXiv cs.AIresearchResponse Variability and Stability in Human Reasoning
arXiv:2610.03008v1 Announce Type: cross Abstract: Understanding how humans reason -- and how reasoning responses vary across tasks and individuals -- remains a core challenge for modeling and explanation in cognitive sci…
- arXiv cs.AIresearchEfficient Analog-Initialized Latent Transport for Spatially Coherent Probabilistic Downscaling from Global to Kilometer Scales
arXiv:2610.03736v1 Announce Type: cross Abstract: Probabilistic downscaling must represent kilometer-scale structure left unresolved by a deterministic regional prediction. We introduce an analog-initialized latent trans…
- arXiv cs.AIresearchLogit-Aware MIMO AirComp for Distributed Mixture-of-Experts LLM Inference over Wireless Edge Networks
arXiv:2610.03741v1 Announce Type: cross Abstract: Distributed mixture-of-experts (MoE) inference is a promising architecture for deploying large language models (LLMs) at wireless edge networks because sparse experts can…
- arXiv cs.AIresearchLoRA Adaptation Strength in Aurora-WRF: Trade-offs in Regional Heavy-Rainfall Forecasting
arXiv:2610.03747v1 Announce Type: cross Abstract: We investigate how parameter-efficient adaptation of an atmospheric foundation model affects downstream regional precipitation in a controlled Aurora-WRF coupling experim…
- arXiv cs.AIresearchGlobal Evaluation of AI and NWP Precipitation Forecasts During Atmospheric River Events
arXiv:2610.03758v1 Announce Type: cross Abstract: Atmospheric rivers (ARs) produce many of the world's most extreme precipitation events and hydrometeorological hazards. Although artificial intelligence weather predictio…
- arXiv cs.AIresearchBridgeCast: Bridging Ocean Wave Forecasts to Reanalysis via Flow Matching with Exogenous Variables
arXiv:2610.03759v3 Announce Type: replace-cross Abstract: Ocean wave forecasting is essential for maritime safety, offshore operations, and coastal resilience, yet remains challenging due to systematic biases in physics-…
- arXiv cs.AIresearchDo Motion Tokenizers for Co-Speech Gesture Generation Encode Gesture Semantics?
arXiv:2610.03765v1 Announce Type: cross Abstract: Discrete motion tokenizers encode motion as atomic units and are widely used for co-speech gesture generation. It remains unclear which motion properties, especially thos…
- arXiv cs.AIagentsOceanMind: A multi-agent AI system for ocean diagnosis
arXiv:2610.03780v1 Announce Type: cross Abstract: Time-dependent, three-dimensional (3D) oceanic multi-variables define coherent states of the evolving ocean to facilitate ocean diagnosis and advance ocean science to bet…
- arXiv cs.AIagentsProsaBuddy: Assisting Mechanized Real-Time Schedulability Analysis with LLM-based Agents
arXiv:2610.03796v1 Announce Type: cross Abstract: Rigorous schedulability analysis is essential for the design of hard real-time systems, yet errors in pen-and-paper proofs threaten the safety of critical applications. T…
- arXiv cs.AIresearchWAMJET: A Harness for World Action Model Acceleration
arXiv:2610.03797v3 Announce Type: replace-cross Abstract: World Action Models (WAMs) leverage pretrained video foundation models for robot manipulation, but their large backbones and video-action co-prediction are expens…
- arXiv cs.AIagentsFrom Requirements to Attack Trees: Grounded LLM Agents for Design-Time Security Review
arXiv:2610.03820v1 Announce Type: cross Abstract: Design-level security weaknesses can arise from requirements, trust assumptions, missing controls, and data flows before implementation begins. Existing security practice…
- arXiv cs.AIresearchThe Score Is Not the Structure: Brain Alignment and Cross-Lingual Transfer
arXiv:2610.03827v4 Announce Type: replace-cross Abstract: Similarity scores are often offered as evidence that a model shares structure with the brain or across languages. We ask what such a score reads when that structu…
- arXiv cs.AIresearchDistribution Matching Evolutionary Algorithms for Rare Event Sampling
arXiv:2610.03833v2 Announce Type: replace-cross Abstract: A novel discovery is one which is both useful and surprising: a generative model's output is a useful discovery if it has a low probability of being generated (it…
- arXiv cs.AIresearchSYNLAT: Syntax-Aligned Text-Latent Compression for Chain-of-Thought Reasoning
arXiv:2610.03839v1 Announce Type: cross Abstract: Long chain-of-thought (CoT) traces impose substantial output-token costs. Under constrained budgets, compression must preserve answer-critical information, making boundar…
- arXiv cs.AIresearchBeware EviLLM: Enabling Vulnerability Injection via Large Language Models
arXiv:2610.03857v1 Announce Type: cross Abstract: Advances in large language models (LLMs) have enabled AI-driven code generation from natural language specifications, introducing new attack surfaces for injecting vulner…
- arXiv cs.AIresearchRetrieval-Centric Deep Learning in Growing Nonparametric Neural Networks
arXiv:2610.03858v1 Announce Type: cross Abstract: We investigate a general-purpose layer for deep learning that, instead of compressing arbitrary-size training data into fixed-size weight matrices, stores a new pair of k…
- arXiv cs.AIresearchGOTT: Object-centric Dexterous Manipulation with a Reusable Cross-Embodiment Primitive
arXiv:2610.03861v2 Announce Type: replace-cross Abstract: Foundation models and large-scale human data provide rich sources of manipulation intent, but translating this intent into multi-fingered robot behavior remains d…
- arXiv cs.AIresearchStreaming Multi-Track Timeline Control for 3D Human Motion Generation
arXiv:2610.03873v2 Announce Type: replace-cross Abstract: Text-driven human motion generation has advanced substantially, yet most methods assume instructions are available before synthesis. Interactive applications requ…
- arXiv cs.AIresearchA Step Towards Forgetting: Optimiser History and the Loss of Answer Mass
arXiv:2610.03940v1 Announce Type: cross Abstract: During fine-tuning, a language model can assign less probability to previously learned answers even when the current gradient acts to preserve that probability. With mome…
- arXiv cs.AIresearchAn Executable Benchmark for LLM-Based HLS Repair:Design Complexity and Repair Underconstraint
arXiv:2610.03971v1 Announce Type: cross Abstract: Automated repair of High-Level Synthesis (HLS) designs using large language models (LLMs) is an emerging but underexplored problem. While LLM-based repair shows strong re…
- arXiv cs.AIresearchSolving VeriContest with a Lean-Backed Rust Verifier
arXiv:2610.03994v2 Announce Type: replace-cross Abstract: VeriContest is a benchmark of 1007 competitive-programming problems in Rust, each with a Verus specification, a judge-accepted solution, and a Verus proof. Its au…
- arXiv cs.AIresearchSelective Backpropagation for Efficient Few-Shot Class-Incremental Learning
arXiv:2610.04003v1 Announce Type: cross Abstract: Few-Shot Class-Incremental Learning (FSCIL) requires models to continuously learn new classes from limited samples while retaining prior knowledge, under strict constrain…
- arXiv cs.AIresearchSlaying the Hydra: Interaction-Aware Circuit Discovery in Language Models
arXiv:2610.04017v1 Announce Type: cross Abstract: Localizing behavior to individual components of a language model is a central goal of mechanistic interpretability. However, scoring components one at a time misses conte…
- arXiv cs.AIresearchMAGEFormer: Learning Metric-Consistent Representations for Anisotropic CT Segmentation
arXiv:2610.04036v1 Announce Type: cross Abstract: Vision Transformers (ViTs) have shown strong performance in volumetric segmentation, but their effectiveness on clinical CT is limited by an isotropic Euclidean lattice a…
- arXiv cs.AIresearchReward-DAgger: Robot-Gated Interactive Imitation Learning with General-Purpose Progress-Based Reward Models
arXiv:2610.04054v1 Announce Type: cross Abstract: Recent advances in robot learning have enabled generalist control policies capable of completing a wide range of tasks. However, their performance degrades when deployed…
- arXiv cs.AIagentsA study on human-agent teaming through spoken interaction: the impact of human individual traits and agent characteristics
arXiv:2610.04079v1 Announce Type: cross Abstract: Human-agent teams are collaborative systems where humans and agents work interdependently to achieve shared goals. The success of such teams is associated with the human'…
- arXiv cs.AIresearchAEGIS: Differentiable Mars Climate Model with Neural Closures
arXiv:2610.04081v1 Announce Type: cross Abstract: General circulation models (GCMs) are the primary tool for simulating planetary atmospheres. They play a vital role in understanding Mars's atmosphere, as forecasting its…
- arXiv cs.AIagentsDependable AI-Assisted Engineering: A Formal Framework for AI Participation and Assurance in Safety-Critical Workflows
arXiv:2610.04084v1 Announce Type: cross Abstract: Generative AI can produce engineering artefacts, but generation alone does not determine whether or how those artefacts should enter safety-critical workflows. This paper…
- arXiv cs.AIagentsDUET: Co-Evolving Solver and Grader Agents
arXiv:2610.04087v1 Announce Type: cross Abstract: Agentic workflows are increasingly used across domains such as technology, finance, and enterprise operations. As these agents become more widely deployed, continually im…
- arXiv cs.AIresearchRobust blind unmixing: A geometric approach to overcoming basis variation
arXiv:2610.04091v1 Announce Type: cross Abstract: Signal separation problems are common in science. A prominent example of this occurs during the use of diffraction or spectroscopy to identify the individual components o…
- arXiv cs.AIresearchSEER: Self-Evolving Event Reasoning and Retrieval for Time Series Forecasting
arXiv:2610.04109v1 Announce Type: cross Abstract: Real-world time series are frequently driven by exogenous events and structural shifts, rendering conventional forecasting based solely on historical numerical observatio…
- arXiv cs.AIagentsAgent Reliability Profiles in Financial Services
arXiv:2610.04123v1 Announce Type: cross Abstract: AI agents can take actions. At times, those actions can go beyond what is intended. Agent reliability can be defined as assurance that an agent will stay within intended…
- arXiv cs.AIresearchRepresentational Control over Self-Report & Behavior Coherence in LLM Risk-Taking
arXiv:2610.04125v1 Announce Type: cross Abstract: Self-report is an appealing low-cost probe of an LLM's dispositions, but recent work finds only selective agreement between what models report and how they behave. Prior…
- arXiv cs.AIagentsPB-GRPO: Learning Socially Adaptive LLM Agents from Persona-Driven Simulation with Preference-Batched GRPO
arXiv:2610.04132v1 Announce Type: cross Abstract: Building LLMs that behave well socially, not merely correctly, requires Building LLMs that behave well socially, not merely correctly, requires more than producing locall…
- arXiv cs.AIagentsAgentic Resource Allocation for Batch Multi-Objective Bayesian Optimization in Autonomous Materials Discovery
arXiv:2610.04134v1 Announce Type: cross Abstract: The discovery and development of advanced materials is a challenging process constrained by the high time and monetary costs of synthesis, processing, and characterizatio…
- arXiv cs.AIresearchDual-Scale Relational Graph Transformers for Ecosystem-Aware Fraud Detection
arXiv:2610.04138v1 Announce Type: cross Abstract: Account takeover (ATO) fraud is a growing threat to digital banking, requiring effective detection while minimizing friction for legitimate customers. Production systems…
- arXiv cs.AIagentsTrajectory-Derived Confidence for Reliable, Resource-Aware Clinical Text-to-SQL Agents
arXiv:2610.04156v1 Announce Type: cross Abstract: LLM agents for clinical text-to-SQL applications reason autonomously over multiple steps but cannot assess whether their own reasoning or outputs can be trusted. In high…
- arXiv cs.AIresearchHow RL Reshapes LLM Reasoning: Transferability, Coverage, and Scaling Laws
arXiv:2610.04158v1 Announce Type: cross Abstract: Recent studies on reinforcement learning (RL) report seemingly conflicting evidence about large language model (LLM) reasoning. Training on mathematics can improve perfor…
- arXiv cs.AIresearchLanguage Model Fingerprinting Requires Rethinking Watermark Teachers
arXiv:2610.04169v1 Announce Type: cross Abstract: LLM fingerprinting via watermark distillation embeds a statistical watermark signal into model weights, enabling model owners to identify their models behind black-box AP…
- arXiv cs.AIresearchRisk-Calibrated Proposal Transport for Finite-Particle Diffusion Steering
arXiv:2610.04171v1 Announce Type: cross Abstract: Inference-time steering combines pretrained diffusion experts or rewards without retraining by changing the dynamics that transport noise to data. Feynman-Kac correction…
- arXiv cs.AIresearchClean: Second-order LLM Training at Linear Memory Cost via Nystr{\"o}m Sketching
arXiv:2610.04204v3 Announce Type: replace-cross Abstract: Training large language models (LLMs) entails a fundamental trade-off: memory-efficient optimizers such as Adam discard cross-parameter curvature, whereas full-cu…
- arXiv cs.AIresearchCurveCodec 2: Skeleton-agnostic animation compression with a learned entropy model
arXiv:2610.04211v1 Announce Type: cross Abstract: Skeletal motion is stored as every joint's transform at every frame, yet most of it is implied by the body rather than by what the motion is about. Compression is one way…
- arXiv cs.AIresearchFTD-GNO: Memory-Efficient Graph Neural Operators through Functional Tensor Decomposition of the Kernel
arXiv:2610.04212v1 Announce Type: cross Abstract: Graph Neural Operators (GNOs) provide flexible surrogate models for learning solution operators of partial differential equations (PDEs). However, standard GNOs typically…
- arXiv cs.AIagentsAdaptive Operator Selection in Bilevel Large Neighborhood Search for Electric Autonomous Dial-a-Ride Problem under Uncertainty
arXiv:2610.04219v1 Announce Type: cross Abstract: The electric autonomous dial-a-ride problem (EADARP) extends the classical dial-a-ride problem by incorporating battery and charging constraints for electric vehicles. In…
- arXiv cs.AIresearchAttention-Based Surface Representation Learning for Robot State Prediction and Open-Ended Surface Classification
arXiv:2610.04240v1 Announce Type: cross Abstract: For ground robots operating in outdoor environments, understanding the properties of the underlying terrain is essential for ensuring reliable operation. In most percepti…
- arXiv cs.AIagentsBenchmarking Psychological Dynamics in Generative Agents
arXiv:2610.04246v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed to simulate human behavior, acting as computational replicas of human subjects. Yet the lived psychological experie…
- arXiv cs.AIagentsPlaying social deduction games with reinforcement fine-tuned large language models
arXiv:2610.04261v1 Announce Type: cross Abstract: Reinforcement fine-tuning (RFT) is increasingly used in applications where large language models (LLMs) interact with humans and other agents. Here we use social deductio…