AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchIntegrating knowledge from case reports: a medical ontology based multimodal information system with structured summary
arXiv:2609.19775v1 Announce Type: new Abstract: Published medical case reports serve as a crucial medical information carrier, documenting discoveries in rare diseases, diagnostic methods, and innovative treatments. Desp…
- arXiv cs.AIagentsContagion on the Trading Floor: How Adversarial Signals Spread in Multi-Agent Trading Systems
arXiv:2609.19789v1 Announce Type: new Abstract: Multi-agent trading systems built on large language models (LLMs) are beginning to appear in quantitative finance, yet their robustness to adversarial inputs is largely unk…
- arXiv cs.AIresearchSteering Equilibrium Selection in Regularized Self-Play via the Reference Policy
arXiv:2609.19820v1 Announce Type: new Abstract: Regularized self-play -- the family behind DeepNash's Stratego play -- drives a two-player zero-sum policy to a Nash equilibrium by best-responding to a slowly moving, entr…
- arXiv cs.AIagentsDual-Axis Policy Optimization for LLM Agents: Bayesian Feedback Attribution and Trajectory Mass Normalization
arXiv:2609.19830v1 Announce Type: new Abstract: Reinforcement learning for LLM agents involves two distinct optimization di- mensions: how environment feedback is exploited within a trajectory, and how complete trajector…
- arXiv cs.AIresearchMetaRTL: Meta-path Attention Enhanced Relational Table Learning
arXiv:2609.19832v1 Announce Type: new Abstract: Relational table learning has gained increasing attention with the widespread use of relational databases. Existing methods typically rely on deep GNN or HGNN stacks, leadi…
- arXiv cs.AIagentsA Dual-Process Perspective on Nudge Susceptibility in LLM-Based GUI Agents
arXiv:2609.19843v1 Announce Type: new Abstract: LLM-based GUI agents increasingly act on behalf of users in digital environments that were designed with human users in mind. These graphical user interfaces were designed…
- arXiv cs.AIresearchConstraint-Safe Graph-Context Scoring for Stable Point-Feature Labels Under Text-Width and Accessibility-Inspired Profiles
arXiv:2609.19848v1 Announce Type: new Abstract: Point-feature label placement on interactive maps must reconcile geometric validity, display yield, local placement utility, and stability across camera motion. Accessibili…
- arXiv cs.AIresearchReproducibility is not construct validity: LLM measurement of institutionally situated communication
arXiv:2609.19866v1 Announce Type: new Abstract: High annotation reproducibility does not necessarily imply that an LLM-inferred measure captures the construct it is intended to measure. We test this distinction using a d…
- arXiv cs.AIresearchPhysical knowledge on historical data matters more than enforcing physical constraints on the forecast
arXiv:2609.19871v1 Announce Type: new Abstract: Time series forecasting has seen signicant advancements with the emergence of new deep learning models. However, forecasting time series in applications involving physical…
- arXiv cs.AIagentsTRACE: Accountable Agentic Retrieval for Source Discovery in Digital Archives
arXiv:2609.19897v1 Announce Type: new Abstract: Historical archives pose a difficult retrieval problem for retrievalaugmented generation systems: documents are OCR-degraded, heterogeneous across genres and sources, and r…
- arXiv cs.AIresearchFrom "Who Is This User?" to "What Does This Purchase Mean?": A Deployed Pipeline for Semantic User Profiling at Bank Scale
arXiv:2609.19928v1 Announce Type: new Abstract: Per-user LLM inference on transaction histories binds the inference budget linearly to user count, which becomes prohibitive at applied scale. We re-cast attribute inferenc…
- arXiv cs.AIresearchBeyond Depth Truncation: Controlled Evaluation of Depth Utilization in Recursive Language Models
arXiv:2609.19934v1 Announce Type: new Abstract: Depth-recurrent language models iteratively apply a small layer stack, decoupling per-token compute from distinct parameter count. To determine whether such a model genuine…
- arXiv cs.AIagentsMaSCoD: A Multi-Agent Framework for Structural-Context-Guided Candidate Causal Graph Generation
arXiv:2609.19944v1 Announce Type: new Abstract: Large language models (LLMs) have been applied to causal discovery, but candidate-graph generation rarely treats premature omission of potentially relevant causal relations…
- arXiv cs.AIagentsNot All AI Agents Are Equal: Characterizing Resource and Performance Dynamics
arXiv:2609.19947v2 Announce Type: replace Abstract: LLM-based AI agents process user requests through iterative reasoning and tool execution, often involving the invocation of remote LLM APIs with local tool containers.…
- arXiv cs.AIagentsNeuro-Symbolic Agentic AI for Networked Low-Altitude UAVs
arXiv:2609.19961v1 Announce Type: new Abstract: Networked low-altitude unmanned aerial vehicles (UAVs) need reliable and adaptive decision-making capabilities to operate under uncertain observations, dynamic environments…
- arXiv cs.AIresearchCustomizable and Jointly Optimized Route Planning: A Deep Architecture Enabling Differentiable Shortest-Path Search
arXiv:2609.19996v1 Announce Type: new Abstract: With the widespread use of online navigation and ride-hailing services, achieving optimal route planning for diverse user preferences has recently attracted increasing atte…
- arXiv cs.AIresearchE-AVI: Evidence-Grounded Multimodal Assessment for Automated Video Interviews
arXiv:2609.20001v1 Announce Type: new Abstract: Automated video interview assessment integrates verbal content, acoustic delivery, and visual behavior, yet numerical predictions alone provide limited inspectable support.…
- arXiv cs.AIresearchGeopolitical Divisions Across Languages in Large Language Models
arXiv:2609.20005v1 Announce Type: new Abstract: People increasingly turn to AI chatbots for news and explanations of world events. But do they receive the same political answers when they ask in different languages? Here…
- arXiv cs.AIresearchFedeRICo: Federated Region-Influenced Coupling for Traffic Flow Prediction
arXiv:2609.20026v1 Announce Type: new Abstract: Urban traffic forecasting often relies on information distributed across stakeholders who may be unable to share raw data due to privacy or commercial constraints, motivati…
- arXiv cs.AIresearchCan Data Attribution Filter Out Subliminal Learning? Not Reliably
arXiv:2609.20027v1 Announce Type: new Abstract: Subliminal learning allows language models to transmit behavioral traits through training data with no obvious semantic relationship to those traits, undermining content-ba…
- arXiv cs.AIresearchDART: Distillation-Aware Reparameterization for Training-Free LoRA Reuse in Few-Step Video Diffusion Models
arXiv:2609.20051v2 Announce Type: replace Abstract: Few-step distillation reduces the inference cost of image-to-video generation, but directly reusing LoRA adapters trained for long denoising trajectories can weaken the…
- arXiv cs.AIresearchMAGMA-GEN: Validated Recovery Supervision from Ambiguous Failures via Counterfactual Re-Execution
arXiv:2609.20056v1 Announce Type: new Abstract: Hierarchical robotic systems executing long-horizon manipulation tasks must make high-level semantic decisions that orchestrate stochastic low-level skills. In this setting…
- arXiv cs.AIresearchWiCleanData: Guaranteeing the Type Consistency of Wikidata by Taxonomy Refinement and Constraint Enforcement
arXiv:2609.20057v1 Announce Type: new Abstract: Because of its collaborative nature, Wikidata suffers from errors, in- consistencies, and excessive complexity, such as redundant classes, ambiguity between instances and c…
- arXiv cs.AIresearchFCA-Guided Counterfactual Explanations for Multi-Modal Breast Cancer Diagnosis: A Framework Achieving Perfect Validity with Emergent Sparsity
arXiv:2609.20067v1 Announce Type: new Abstract: Deep learning models for multi-modal breast cancer diagnosis achieve high predictive accuracy but remain clinically unacceptable without actionable, counterfactual explanat…
- arXiv cs.AIresearchMarginal utility, matrix factorization, and the Key-Value (KV) cache: a unified information-economic framework for sovereign geo-mining inference
arXiv:2609.20068v1 Announce Type: new Abstract: This paper builds a theoretical bridge between the economic notion of marginal utility and two machine-learning constructs, matrix factorization and the Key--Value cache of…
- arXiv cs.AIresearchTailored to you: longitudinal effects of personalising language models
arXiv:2609.20077v2 Announce Type: replace Abstract: Interest in developing personalised language models is rapidly growing. While personalisation is often viewed as a mechanism to better serve diverse user needs, the eff…
- arXiv cs.AIagentsA Proposal for an Agentic AI Architecture to Support Multi-Domain Decision-Making in the Brazilian Armed Forces
arXiv:2609.20080v1 Announce Type: new Abstract: The growing complexity of multi-domain operational environments (land, aerospace, naval, cyber, and electromagnetic spectrum) has increased the volume and velocity of data…
- arXiv cs.AIagentsUnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
arXiv:2609.20089v1 Announce Type: new Abstract: Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing methods typically sep…
- arXiv cs.AIresearchSolving Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling Problems
arXiv:2609.20091v1 Announce Type: new Abstract: The Antibandwidth and Cyclic Antibandwidth problems are NP-hard graph labeling problems that aim to maximize the minimum (cyclic) distance between labels assigned to adjace…
- arXiv cs.AIresearchPerception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documents
arXiv:2609.20110v1 Announce Type: new Abstract: Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together with a bounded guar…
- arXiv cs.AIagentsMTVA-Bench: Evaluating the Language Model Inside Cascaded Voice Agents
arXiv:2609.20152v1 Announce Type: new Abstract: Generally, most voice agents are cascaded systems, i.e., an ASR model transcribes the caller's audio, a language model reads the transcript and decides what to say and whic…
- arXiv cs.AIresearchPaGNet: A Panel-Aware GBDT--Neural Network for Multi-Target Corporate Tax Avoidance Proxy Forecasting
arXiv:2609.20177v1 Announce Type: new Abstract: Forecasting corporate tax avoidance proxies from firm--year panel data is challenging because predictive signals are distributed across short firm histories and related tar…
- arXiv cs.AIresearchSequential Contextual Fit Predicts Human Behavioural and Neural Dynamics Across Domains
arXiv:2609.20179v1 Announce Type: new Abstract: Human perception, action and decision making unfold in sequences, but computational predictors are often domain-specific. This study computes and tests sequential contextua…
- arXiv cs.AIresearchJointMatch: A Unified Heterogeneous Graph Neural Solver for Large-Scale Ride-Sharing Matching
arXiv:2609.20200v1 Announce Type: new Abstract: Ride-sharing platforms must continuously decide which open requests to bundle into shared trips and which idle vehicles should serve them. The dominant academic approach de…
- arXiv cs.AIagentsWhen AI Agents Commit: Cognitive Serializability Across Data, Evidence, Policy, and Authority
arXiv:2609.20261v1 Announce Type: new Abstract: Autonomous agents derive concrete mutations from database reads, retrieved evidence, policy, beliefs, and delegated authority. Those inputs may change while reasoning is in…
- arXiv cs.AIresearchAI-Driven Real-Time Relay Optimisation in Smart Urban NR-V2X Networks via Learning-to-Optimise Graph Neural Networks
arXiv:2609.20271v1 Announce Type: new Abstract: Reliable and low-latency communication is a fundamental requirement for smart city services and Industry 4.0 applications enabled by NR-V2X networks. However, limited Road-…
- arXiv cs.AIresearchJEPA-WAM: Connecting Generated Visual Instructions to World Action Models through JEPA Latent Representations
arXiv:2609.20277v1 Announce Type: new Abstract: World Action Models (WAMs) have demonstrated strong robotic manipulation capabilities by augmenting pretrained video generative models with action experts. However, current…
- arXiv cs.AIagentsAgentPProf: Semantic Profiler for Long Horizon AI Agents
arXiv:2609.20301v1 Announce Type: new Abstract: AI agents increasingly orchestrate long-running activities with users, tools, and system resources for days and weeks. To improve agent quality, safety, and cost efficiency…
- arXiv cs.AIresearchDiagnose, Recover, Certify: Task Readiness under Hidden Dynamics Changes
arXiv:2609.20304v1 Announce Type: new Abstract: A deployed control policy can conceal consequential dynamics changes: an actuator may lose effectiveness without affecting the current task when the policy rarely excites i…
- arXiv cs.AIresearchNeuSOGA3D: A Neuro-Symbolic Framework for Explainable 3D Geometric Reconstruction
arXiv:2609.20323v2 Announce Type: replace Abstract: Three-dimensional reconstruction from unorganized point clouds remains a challenging problem in computer vision, geometric modeling, and computer-aided design. While ne…
- arXiv cs.AIresearchStructured Four-Stage Legal Translation: From Natural-Language Traffic Rules to PROLOG
arXiv:2609.20334v1 Announce Type: new Abstract: Traffic regulations are written for human interpretation and therefore rely on shared background knowledge and flexible phrasing, which inherently introduce ambiguity, cont…
- arXiv cs.AIresearchA Qualitative Model for Reasoning about Path and Support
arXiv:2609.20349v1 Announce Type: new Abstract: Spatial reasoning abilities correlate strongly with performance in STEM fields. Games offer a compelling medium for training these critical skills in developing children wh…
- arXiv cs.AIresearchGenerating Heterogeneous 3D Geological Microstructures from 2D Images via a Stable Diffusion-Adversarial Model
arXiv:2609.20358v1 Announce Type: new Abstract: Characterizing the physical properties of clay and cementitious materials matters across many fields, from materials science to geological waste disposal. Property simulati…
- arXiv cs.AIagentsThe Organization of Inference: Information, Resource Constraints, and AI Production
arXiv:2609.20449v1 Announce Type: new Abstract: The economic value of inference depends on how capacity and task information are distributed across stages of AI production. We study these organizational margins using con…
- arXiv cs.AIresearchGraphSkillAA: Attribution-Guided Skill-Graph Updating with Targeted Validation and Rollback
arXiv:2609.20455v2 Announce Type: replace Abstract: External skills provide domain knowledge and procedures without updating model parameters, but flat collections obscure skill applicability, dependencies, and compositi…
- arXiv cs.AIagentsHow Do Agent Harnesses Create Value? Planning Information and Release Control in Stateful LLM Agents
arXiv:2609.20474v1 Announce Type: new Abstract: Agent harnesses supply planning guidance, organize execution, and check completion. We study how these components affect success, erroneous acceptance, and cost in two Reta…
- arXiv cs.AIagentsSoL-Pi: Recursively Scaling Auto-Research Loops for Efficient Agent Harness
arXiv:2609.20519v1 Announce Type: new Abstract: As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into long trajectories of re…
- arXiv cs.AIresearchFreqCondNorm: Towards Cross-domain Predictive Maintenance through a Frequency-Conditioned Transformer Foundation Model
arXiv:2609.20535v1 Announce Type: new Abstract: Deep learning predictive maintenance models suffer from poor transferability across machines and operating conditions, especially when labelled data are scarce and signals…
- arXiv cs.AIresearchRefuse, Decompose, Refresh: A Claim-Safe Protocol for Closed-Loop AI Evaluation
arXiv:2609.20538v1 Announce Type: new Abstract: An AI evaluation can be perfectly reproducible and still support the wrong claim. This risk is acute in closed-loop systems: policy determines visited states, observable co…
- arXiv cs.AIresearchLanguage-model groups overstate consensus when replaying human deliberation on a reasoning task
arXiv:2609.20543v1 Announce Type: new Abstract: Full-consensus rates are often treated as indicators of collective cognition, yet depend on how participation and final states are operationalized. We replayed 100 held-out…