AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchTask-Utility IQA: Rethinking Image Quality Assessment in Embodied Tasks
arXiv:2610.35905v1 Announce Type: cross Abstract: Image quality assessment (IQA) underpins embodied imaging pipelines by judging whether visual quality satisfies downstream tasks, yet most existing methods learn task-agn…
- arXiv cs.AIresearchPhysiognomy Revisited: How Vision-Language Models Encode Sensitive Attributes Through Image Transformation
arXiv:2610.35910v1 Announce Type: cross Abstract: Emergent generative AI technologies, while remarkably beneficial across several tasks and domains, can suffer from unforeseen vulnerabilities and difficult-to-anticipate…
- arXiv cs.AIresearchReCoPII: A Relation-Grounded Framework for Building Contextual PII Masking Datasets
arXiv:2610.35925v1 Announce Type: cross Abstract: Training contextual masking systems for personally identifiable information (PII) requires examples distinguishing maskable from preservable mentions of one entity type,…
- arXiv cs.AIagentsSCOPE: Source Credibility and Outlet Profiling Engine
arXiv:2610.35929v1 Announce Type: cross Abstract: We present SCOPE, a multi-agent system for profiling news media outlets with respect to bias, factuality, and credibility. Given an outlet URL, SCOPE coordinates speciali…
- arXiv cs.AIagentsWho Convinced Whom? Tracing How LLMs Change Their Minds in Multi-Agent Systems
arXiv:2610.35930v1 Announce Type: cross Abstract: Multi-agent debate (MAD) aims to improve language-model decisions through the exchange of arguments, yet agreement after debate need not reflect independent corroboration…
- arXiv cs.AIagentsCurriculum-Driven Deep Reinforcement Learning for Autonomous Far-Range Rocket Landing
arXiv:2610.35954v1 Announce Type: cross Abstract: Autonomous vertical landing of reusable launch vehicles is a critical yet formidable challenge in aerospace engineering, primarily due to highly nonlinear dynamics, strin…
- arXiv cs.AIresearchResCom: Activation Residual Compensation for Large Language Model Quantization
arXiv:2610.35955v1 Announce Type: cross Abstract: Low-bit weight--activation quantization reduces the memory and computation needed to deploy large language models, but activation rounding can still degrade accuracy afte…
- arXiv cs.AIresearchStructured Time-Frequency Representation for Channel Prediction
arXiv:2610.35956v1 Announce Type: cross Abstract: Accurate CSI forecasting is essential for mitigating channel aging and supporting reliable downlink transmission in high-mobility wireless systems. In FDD systems, foreca…
- arXiv cs.AIagentsAgentBaton: Efficient Model Collaboration in Agentic Tasks
arXiv:2610.35959v1 Announce Type: cross Abstract: Solving long-horizon agentic tasks requires language agents to interact with their environments over multiple steps, and reliable performance often comes from the expensi…
- arXiv cs.AIagentsA Hyper-Logical View on Multi-Agent Path Planning
arXiv:2610.35964v1 Announce Type: cross Abstract: Multi-Agent Path Planning (MAPP) requires collision-free paths for multiple agents. MAPP has numerous real-life applications, including the navigation of automated vehicl…
- arXiv cs.AIagentsEMMA: Structured Episodic Memory for Multi-Agent Workflow Synthesis
arXiv:2610.35966v1 Announce Type: cross Abstract: Deploying LLM agents in specialized domains often require fine-grained task-specific procedures and knowledge a general model lacks, yet parameter training is costly and…
- arXiv cs.AIresearchMultiple Leak Localization in Water Distribution Networks through Graph Neural Networks
arXiv:2610.35972v1 Announce Type: cross Abstract: Leak localization in water distribution networks is challenging when multiple leaks occur simultaneously, particularly under sparse monitoring. Existing data-driven metho…
- arXiv cs.AIagentsUnityBench-Mini3D: Evaluating LLM Agents for 3D Game Development in Unity
arXiv:2610.35980v1 Announce Type: cross Abstract: Game development stresses coding agents in ways general software engineering does not: correctness depends on how engine APIs, serialized scene state, and runtime behavio…
- arXiv cs.AIagentsGeneration and Verification: Human-Agent Collaboration for Safety-Critical Automotive Software Engineering
arXiv:2610.35982v1 Announce Type: cross Abstract: Research on coding agents mainly focuses on generation quality. Yet, safety-critical automotive software makes two additional demands. It prioritizes verification, since…
- arXiv cs.AIresearchLet the Gate Decide: Per-Lookup Precision for Quantized Conditional Memory in LLMs
arXiv:2610.35985v1 Announce Type: cross Abstract: Conditional memory layers, such as DeepSeek's Engram, attach large hashed n-gram tables to a language model, and removing them from DeepSeek-V4.1-Flash costs 36.8 PopQA p…
- arXiv cs.AIagentsPROBE: Frontier Coding Agents Find Different Bugs Than Maintainers Fix
arXiv:2610.35987v1 Announce Type: cross Abstract: Proactive bug discovery is an important software-engineering problem. Even though coding agents are already widely deployed in this domain, their capabilities remain unde…
- arXiv cs.AIresearchLayerwise Repacking: Variable-Length Hybrid-Attention Training without an Extra Redistribution Pass
arXiv:2610.35989v1 Announce Type: cross Abstract: Variable-length training creates conflicting parallelism requirements across the layers of a hybrid-attention model. The longest samples require wide sequence-parallel (S…
- arXiv cs.AIresearchPricing Cross-Bank Context in Federated Anti-Money Laundering
arXiv:2610.35996v1 Announce Type: cross Abstract: Most graph-based Anti-Money Laundering (AML) methods assume access to a pooled transaction graph containing all accounts and payments, which in reality does not exist. Fe…
- arXiv cs.AIagentsPolicyMediator: Multi-Regional Policy Learning through Mediation Agents with Evolving Skills in OPC Ecosystems
arXiv:2610.35997v1 Announce Type: cross Abstract: One-person companies (OPCs) are emerging enterprises operated by individual entrepreneurs through digital platforms and LLM-based AI agents. These highly skilled entrepre…
- arXiv cs.AIresearchMedJev: Evaluating Zero-Shot System-One Decision Making in Medicine
arXiv:2610.36006v1 Announce Type: cross Abstract: System One decision models such as Jev answer structured questions in a single forward pass without generating text, offering fast and computationally efficient clinical…
- arXiv cs.AIresearchDuplexTune: Coupled-State Replay for Memory-Efficient Mixture-of-Experts Adaptation
arXiv:2610.36009v1 Announce Type: cross Abstract: Sparse expert execution does not remove the stored states needed to adapt a mixture-of-experts language model. We present DuplexTune, a framework for replaying coupled hi…
- arXiv cs.AIagentsCIVER: Causal Intervention Verification for Reliable Code Review
arXiv:2610.36010v1 Announce Type: cross Abstract: Code review is essential for maintaining software repositories by identifying defects, improving code quality, and supporting reliable software evolution. With the growin…
- arXiv cs.AIagentsDo Coding Agents Still Need a Debugger? Frontier-Model-Based Fault Localization at the Accuracy Ceiling
arXiv:2610.36015v1 Announce Type: cross Abstract: Background: To localize a fault, a coding agent can reason from source code alone or use debugger assistance by running the program and stepping through it in an interact…
- arXiv cs.AIresearchRollback: Experience Backtracking in World Models for Policy Improvement
arXiv:2610.36068v1 Announce Type: cross Abstract: Action-conditioned world models offer a scalable alternative to costly real-world interaction for improving robot policies. However, existing world-model-based methods la…
- arXiv cs.AIresearchHow Much Does the Hint Matter? Scope Conditions for Hindsight Self-Distillation in Financial Reasoning
arXiv:2610.36082v1 Announce Type: cross Abstract: Financial institutions operating under data-residency constraints are restricted to open-weight models small enough to locally host, which trail frontier systems on multi…
- arXiv cs.AIagentsLog-To-Leak: Prompt Injection Attacks on Tool-Using LLM Agents via the Model Context Protocol
arXiv:2610.36108v1 Announce Type: cross Abstract: LLM agents increasingly access external tools through the Model Context Protocol (MCP), but the natural-language metadata used to describe those tools creates a prompt-in…
- arXiv cs.AIresearchDirichlet Process Mixtures within Semiparametric Bayesian Networks: A Novel Conditional Density Estimation Approach
arXiv:2610.36110v1 Announce Type: cross Abstract: Semiparametric Bayesian networks (SPBNs) are flexible probabilistic graphical models for representing joint distributions of continuous variables through lower-dimensiona…
- arXiv cs.AIresearchScaling and Renormalization in Neural Networks: An Effective Renormalization-Group Description of Grokking
arXiv:2610.36113v1 Announce Type: cross Abstract: Grokking is a delayed transition from memorization to generalization in deep neural networks (NNs). We examine whether scaling and renormalization group (RG) theories can…
- arXiv cs.AIagentsContext Is a Pipeline, Not a Window: Information Attrition in LLM Agent Harnesses
arXiv:2610.36114v1 Announce Type: cross Abstract: LLM agents are judged by two numbers: the size of the context window, and how often the final answer is correct. Both numbers miss a third thing: how much of a tool's out…
- arXiv cs.AIagentsWhen Connectivity Misleads: Guiding Agentic Search with Contrastive Evidence Paths
arXiv:2610.36134v1 Announce Type: cross Abstract: Search agents can use cross-document graphs to discover sources through multi-hop connections and choose subsequent actions based on candidate rankings and relationships…
- arXiv cs.AIresearchPhysical structure as an organizing principle for universal Hamiltonian learning
arXiv:2610.36135v1 Announce Type: cross Abstract: Density functional theory (DFT) gives the electronic structure of materials, but its cost limits large-supercell calculations and materials screening. Machine-learned Ham…
- arXiv cs.AIagentsReplication or Corroboration? An Axiomatic Framework for Evidential Dependence in Multi-Agent Debate
arXiv:2610.36151v1 Announce Type: cross Abstract: In multi-agent debates, matching reports can arise for two different reasons: agents may repeat the same evidence (replication), or they may provide separate evidential r…
- arXiv cs.AIagentsStratum: Repository Memory for Coding Agents Beyond the Context Window
arXiv:2610.36153v1 Announce Type: cross Abstract: Context windows have grown a thousand-fold, yet coding agents still start every session with no memory of their past work. They re-read files, retry failed approaches, an…
- arXiv cs.AIagentsCan AI Guide Testing Without Generating Tests? A Comparative Study of AI-Assisted Unit Testing
arXiv:2610.36185v1 Announce Type: cross Abstract: Recent advances in generative AI have enabled assistants to generate increasingly sophisticated executable unit tests. However, novices may accept these outputs without i…
- arXiv cs.AIresearchBeyond the Estimate: Wiener-Informed Decoding for Easier Training of Pixel-Space Flow Models
arXiv:2610.36192v1 Announce Type: cross Abstract: Learning velocity fields directly in pixel space is difficult and slow. We show that coarse second-order image statistics can ease this task: frozen Wiener estimates impr…
- arXiv cs.AIresearchcount-catcher: Lean Theorems from Model Counting Certificates
arXiv:2610.36196v1 Announce Type: cross Abstract: We present count-catcher, a tool that turns a CPOG certificate of a count by the exact model counter d4 into a Lean theorem that a CNF formula defined in Lean has exactly…
- arXiv cs.AIresearchBase Models Can Detect Hidden Intentions that Prompted Classifiers Miss
arXiv:2610.36202v1 Announce Type: cross Abstract: The Persona Selection Model (PSM) posits that post-training selects a persona the model learned during pre-training. Work on subliminal learning has shown that models can…
- arXiv cs.AIresearchConcorde: Geometry-Aware Link Prediction via Decoupled Energy Minimization
arXiv:2610.36204v1 Announce Type: cross Abstract: Link prediction remains difficult in sparse graphs, where diffusion heuristics lack connectivity and geometric methods suffer spectral instability when coupling learned r…
- arXiv cs.AIresearchCounterfactual Profile Perturbations for Recommendation Explanations: A Reproducibility Study
arXiv:2610.36208v1 Announce Type: cross Abstract: This reproducibility paper explores the counterfactual explanation technique known as Learning to eXplain Recommendations (LXR). Prior work has shown that LXR can reliabl…
- arXiv cs.AIresearchStructure, Not Sequence: Tracking and Validating Folding Mechanisms in ESMFold's Trunk with Sparse Autoencoders
arXiv:2610.36226v1 Announce Type: cross Abstract: Structure predictors like ESMFold fold proteins using neural network computation and have transformed structural biology. However, the driving mechanism from amino-acid (…
- arXiv cs.AIresearchDirectional Statistics on Circles and Spheres: A New Angle on Data
arXiv:2610.36227v1 Announce Type: cross Abstract: Two compass bearings near north can have an ordinary arithmetic mean pointing south: the difficulty is that angles live on a circle, not a straight line. Using real wind…
- arXiv cs.AIagentsAgent or Human? Detecting Commits by AI Coding Agents in the Absence of Authorship Signatures
arXiv:2610.36229v1 Announce Type: cross Abstract: AI coding agents such as Claude Code, GitHub Copilot coding agent, and Cursor now commit directly to open-source repositories. Empirical studies of these agents identify…
- arXiv cs.AIresearchFreeze, Don't Clone: Fine-Tuning with Expressive Policies Without Retaining Offline Data
arXiv:2610.36247v1 Announce Type: cross Abstract: Offline-to-online reinforcement learning uses offline pretraining to accelerate subsequent online learning. While many methods assume the offline dataset remains availabl…
- arXiv cs.AIresearchcuArms: GPU-Accelerated Conflict-Based Planning for Multi-Arm Manipulation
arXiv:2610.36250v1 Announce Type: cross Abstract: Multi-arm manipulation has the potential to dramatically improve the throughput, efficiency, and dexterity of many manipulation tasks. Recent work coordinates multiple ro…
- arXiv cs.AIagentsBUSTA: Teaching Small Language Models to Reason About Binary Execution
arXiv:2610.36288v1 Announce Type: cross Abstract: Large Language Models (LLM) are increasingly applied to Reverse Engineering (RE) workflows. RE, however, differs from common LLM coding tasks as it requires models to rea…
- arXiv cs.AIresearchDetecting and Mitigating Query-Based System Prompt Leakage Attacks
arXiv:2610.36295v1 Announce Type: cross Abstract: Large Language Models (LLMs) rely on proprietary system prompts to enforce task directives, safety policies, and access controls. These prompts are vulnerable to query-ba…
- arXiv cs.AIresearchCrowdCC: Jointly Benchmarking Corruption Robustness and Deployment Quantization in Crowd Counting
arXiv:2610.36340v2 Announce Type: replace-cross Abstract: Crowd-counting models deployed on edge devices face two challenges: inputs are degraded along the capture and transmission pipeline, while models are often quanti…
- arXiv cs.AIresearchEnhancing Clinical Classifier Robustness with Deep Representation Learning Based OOD Detection on DNA Methylation Data
arXiv:2610.36344v1 Announce Type: cross Abstract: DNA methylation (DNAM) array-based tumor classification is a powerful clinical diagnostic tool, but models trained on fixed reference cohorts can produce faulty predictio…
- arXiv cs.AIresearchReliability-Aware Short-Term Glycemic Risk Prediction Using an Anchor-Based Comparative Framework of Sequence, Multimodal, and State-Updating Digital-Twin Models
arXiv:2610.36363v1 Announce Type: cross Abstract: Anticipating short-term hypoglycemic and hyperglycemic risk is essential for proactive diabetes management. However, existing machine learning approaches often use incons…
- arXiv cs.AIagentsHIDRA: Hierarchical Dual-Routing Attention for Replay-Free Lifelong Imitation Learning
arXiv:2610.36374v1 Announce Type: cross Abstract: Robotic agents operating in real-world environments must adapt continuously from a stream of multimodal demonstrations, often under constraints that preclude storing or r…