AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSpatial disparities in simulated patrol detection: a reproducible generative-model audit across Baltimore and Chicago
arXiv:2603.18987v3 Announce Type: replace Abstract: Auditing predictive policing requires distinguishing recorded crime incidents, simulated patrol observations, and the demographic characteristics of places. We present…
- arXiv cs.AIresearchUncertainty-Guided Latent Diagnostic Trajectory Learning for Sequential Clinical Diagnosis
arXiv:2604.05116v2 Announce Type: replace Abstract: Clinical diagnosis requires sequential evidence acquisition under uncertainty. However, most Large Language Model (LLM) based diagnostic systems assume fully observed p…
- arXiv cs.AIagentsMCPHunt: An Evaluation Framework for Cross-Boundary Data Propagation in Multi-Server MCP Agents
arXiv:2604.27819v2 Announce Type: replace Abstract: Multi-server MCP agents create an information-flow control (IFC) problem: faithful tool composition can turn individually benign read/write permissions into cross-bound…
- arXiv cs.AIagentsAgents and Tokens: Multi-Agent Autonomous Reasoning over a Hydrodynamic Token Store
arXiv:2605.01102v2 Announce Type: replace Abstract: Large language models and the agents built on them are the most capable reasoning machines ever built, and science is beginning to put them to work. Atmospheric and oce…
- arXiv cs.AIagentsModel-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use
arXiv:2605.14038v3 Announce Type: replace Abstract: Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke external tools. Prior work studying adapt…
- arXiv cs.AIagentsNeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
arXiv:2605.16757v2 Announce Type: replace Abstract: Multi-agent language systems are often built as hand-designed workflows, where agents are assigned semantic roles and communication protocols are specified in advance.…
- arXiv cs.AIresearchNoise-Robust Financial Numerical Entity Attribute Tagging
arXiv:2605.24910v2 Announce Type: replace Abstract: Financial Numerical Entity (FNE) understanding aims to recover the meaning of numerical mentions in financial reports. Existing studies focus on concept name prediction…
- arXiv cs.AIresearchCan Broad Biomedical Knowledge be Contextualized into Scenario-Grounded Propositions?
arXiv:2605.27082v2 Announce Type: replace Abstract: Biomedical discovery often requires connecting broad biomedical knowledge with specific experimental or clinical data. Background knowledge suggests relevant mechanisms…
- arXiv cs.AIresearchSame Answer, Different Confidence: Protocol Sensitivity in LLM Confidence Calibration
arXiv:2605.27752v4 Announce Type: replace Abstract: Large language models (LLM) can state their confidence in an answer (verbalized confidence), or the confidence can be read from the probability of the answer's tokens (…
- arXiv cs.AIagentsProbe Before You Edit: Probing-Guided Molecular Optimization for LLM Agents in Structure-Based Drug Design
arXiv:2606.00555v3 Announce Type: replace Abstract: Structure-based drug design increasingly employs LLM agents to iteratively refine ligands against a target pocket, yet a viable ligand must satisfy two often-conflictin…
- arXiv cs.AIagentsSkillPyramid: A Hierarchical Skill Consolidation Framework for Self-Evolving Agents
arXiv:2606.03692v2 Announce Type: replace Abstract: Recent AI agents can flexibly invoke skills to solve complex tasks, but their long-term improvement is fundamentally constrained by a lack of systematic skill construct…
- arXiv cs.AIagentsArchitecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning
arXiv:2606.11634v2 Announce Type: replace Abstract: The rapid progress of reasoning and agentic large language models (LLMs) has increased the demand for long-context inference, but self-attention (SA) scales quadratical…
- arXiv cs.AIresearchTrust the Right Teacher: Quality-Aware Self-Distillation for GUI Grounding
arXiv:2606.18101v3 Announce Type: replace Abstract: GUI grounding requires vision-language models (VLMs) to identify small target elements in high-resolution screenshots and predict precise screen coordinates. On-policy…
- arXiv cs.AIresearchDeFAb: A Dataset for Grounded Scientific Discovery through Defeasible Abduction
arXiv:2606.18557v2 Announce Type: replace Abstract: A theory can accommodate a counterexample by adding an exception. The harder problem is deciding how far the exception should extend and which predictions should surviv…
- arXiv cs.AIagentsAlphaMemo: Structured Search-Process Memory for Self-Evolving Alpha Mining Agents
arXiv:2606.20625v2 Announce Type: replace Abstract: LLM agents are promising for alpha mining via combining financial priors, symbolic reasoning, executable factor generation, and feedback-driven refinement. Yet, they fa…
- arXiv cs.AIresearchAttractor Domain Theory: A Mathematical Framework for Cardiovascular Attractor Analysis with Wearable Photoplethysmography (PPG) Validation
arXiv:2606.22039v3 Announce Type: replace Abstract: The cardiac attractor provides a phase-space representation of cardiovascular dynamics reconstructed from scalar observations under standard delay-embedding conditions.…
- arXiv cs.AIresearchDeepSafe-SciHazard: A Benchmark for Measuring Scientific Safety Risks with Decomposed Harm Scoring
arXiv:2607.18665v2 Announce Type: replace Abstract: Large language models (LLMs) increasingly support science, but they can also convert hazardous scientific knowledge into actionable misuse guidance. Existing benchmarks…
- arXiv cs.AIagentsJANUS: Foreseeing Latent Risk for Long-Horizon Agent Safety
arXiv:2607.19913v2 Announce Type: replace Abstract: Agent safety is moving from content moderation toward preventing operational failures before tool-using agents act. We propose Janus, a foresight-oriented framework for…
- arXiv cs.AIresearchWhere Cross-Question Structure in LLM Errors Comes From: Shared Seeds, Shared Prompts, and Answer-Letter Preference
arXiv:2607.20464v2 Announce Type: replace Abstract: Disagreement between language models is often read as missing knowledge. Questions that need the same missing knowledge should then be right or wrong together. We test…
- arXiv cs.AIresearchShapes from Examples: Foundations of Shape Learning in Recursive SHACL
arXiv:2607.27934v3 Announce Type: replace Abstract: SHACL shapes enable data graph validation, making automatic shape learning essential for knowledge graph applications. We investigate the well-known fitting approach to…
- arXiv cs.AIagentsMirrorCraft: Paired Evaluation under Hidden Rule Changes in Minecraft
arXiv:2607.29218v2 Announce Type: replace Abstract: With the rapid progress of large language models (LLMs), an interesting question has emerged: how do LLM-based agents perform in Minecraft? To date, most Minecraft benc…
- arXiv cs.AIresearchAI-guided deep visual proteomics reveals recurrence-associated morpho-molecular signatures within triple-negative breast cancers
arXiv:2608.03145v3 Announce Type: replace Abstract: Outcome informed AI can localize prognostically relevant regions in digital pathology, but directly characterizing the molecular basis of these spatial predictions rema…
- arXiv cs.AIresearchTreeWY: Speculative Verification for Gated DeltaNet Hybrids
arXiv:2608.20961v2 Announce Type: replace Abstract: Modern open models are hybrids: most layers are linear-attention (Gated DeltaNet, GDN) layers carrying a small fixed-size recurrent state instead of a growing key-value…
- arXiv cs.AIagentsInterchangeable in Role, Not in History: Replacing Members of Formed LLM Teams
arXiv:2609.05279v2 Announce Type: replace Abstract: Multiagent LLM systems often treat a role as a slot: when a member is replaced, any agent competent at the role is expected to fill it. We test this view on teams whose…
- arXiv cs.AIresearchOn Orthogonal Recurrent Neural Networks Quantization
arXiv:2402.04012v3 Announce Type: replace-cross Abstract: In recent years, Orthogonal Recurrent Neural Networks (ORNNs) have gained popularity due to their ability to manage tasks involving long-term dependencies, such a…
- arXiv cs.AIresearchPower- and Fragmentation-aware Online Scheduling for GPU Datacenters
arXiv:2412.17484v2 Announce Type: replace-cross Abstract: The rise of Artificial Intelligence and Large Language Models is driving increased GPU usage in data centers for complex training and inference tasks, impacting o…
- arXiv cs.AIresearchEnhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner
arXiv:2412.20662v4 Announce Type: replace-cross Abstract: Pre-trained foundation models have recently made significant progress in table-related tasks such as table understanding and reasoning. However, recognizing the s…
- arXiv cs.AIresearchCatastrophic Overfitting, Entropy Gap and Participation Ratio: A Noiseless $l^p$ Norm Solution for Fast Adversarial Training
arXiv:2505.02360v3 Announce Type: replace-cross Abstract: Adversarial training is a cornerstone of robust deep learning, but fast methods like the Fast Gradient Sign Method (FGSM) often suffer from Catastrophic Overfitti…
- arXiv cs.AIresearchDeep Learning Warm Starts for Trajectory Optimization on the International Space Station
arXiv:2505.05588v4 Announce Type: replace-cross Abstract: Trajectory optimization is a cornerstone of modern robot autonomy, enabling systems to compute trajectories and controls in real-time while respecting safety and…
- arXiv cs.AIresearchAU-Harness: An Open-Source Toolkit for Efficient and Unified Evaluation of AUdio-LLMs
arXiv:2509.08031v4 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) are rapidly advancing, but evaluating them remains challenging due to inefficient and nonstandardized toolkits that limit fair…
- arXiv cs.AIresearchDynamic Relational Priming Improves Transformer in Multivariate Time Series
arXiv:2509.12196v3 Announce Type: replace-cross Abstract: Standard attention mechanisms in transformers employ static token representations that remain unchanged across all pair-wise computations in each layer. This limi…
- arXiv cs.AIresearchHuman-AI Interactions and the Psychological Triad: A Multi-Domain Survey of Cognitive, Behavioral, and Emotional Impacts
arXiv:2510.17753v3 Announce Type: replace-cross Abstract: As human-AI interactions increasingly reshape social and research landscapes, the risks of overreliance, cognitive offloading, and the nuanced degradation of huma…
- arXiv cs.AIresearchBeyond the Monolithic Scheduler: Lightweight Adaptive Policy Switcher for Process Scheduling Optimization
arXiv:2511.11628v2 Announce Type: replace-cross Abstract: Modern operating system process schedulers typically enforce a static, ``one-policy-fits-all'' design, which inevitably compromises performance under the highly d…
- arXiv cs.AIresearchEvalCards: A Framework for Standardized Evaluation Reporting
arXiv:2511.21695v2 Announce Type: replace-cross Abstract: Evaluation reports guide the use of general-purpose AI (GPAI) models, yet inconsistent reporting often leaves essential questions unanswered. Through a review of…
- arXiv cs.AIresearchDementia-R1: Reinforced Pretraining and Reasoning from Unstructured Clinical Notes for Real-World Dementia Prognosis
arXiv:2601.03018v3 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) have shown strong performance on clinical text understanding, they struggle with longitudinal prediction tasks such as dementia…
- arXiv cs.AIresearchThe Role of Quantum in Hybrid Quantum-Classical Neural Networks: An Empirical Assessment
arXiv:2601.04732v2 Announce Type: replace-cross Abstract: Quantum machine learning has emerged as a promising application domain for near-term quantum hardware, particularly through hybrid quantum-classical models that l…
- arXiv cs.AIagentsPAIR-SAFE: A Paired-Agent Approach for Runtime Auditing and Refining AI-Mediated Mental Health Support
arXiv:2601.12754v2 Announce Type: replace-cross Abstract: LLMs are increasingly used for mental health support, yet they can produce responses that are overly directive, inconsistent, or clinically misaligned. Most risk…
- arXiv cs.AIresearchAttention-space Contrastive Guidance for Efficient Hallucination Mitigation in LVLMs
arXiv:2601.13707v3 Announce Type: replace-cross Abstract: Hallucinations in large vision--language models (LVLMs) often arise when language priors dominate over visual evidence, leading to object misidentification and vi…
- arXiv cs.AIresearchTowards robust long-context understanding of large language model via active recap learning
arXiv:2601.13734v2 Announce Type: replace-cross Abstract: In this paper, we propose active recap learning (ARL), a framework for enhancing large language model (LLM) in understanding long contexts. ARL enables models to…
- arXiv cs.AIresearchOmniSpectra: A Unified Foundation Model for Universal Spectra Representation Learning
arXiv:2601.15351v2 Announce Type: replace-cross Abstract: Standard sequence models encode position by token rank rather than physical coordinate, typically forcing practitioners to destructively resample continuous physi…
- arXiv cs.AIresearchClifford Kolmogorov-Arnold Networks
arXiv:2602.05977v3 Announce Type: replace-cross Abstract: We introduce Clifford Kolmogorov-Arnold Network (ClKAN), a flexible and efficient architecture for function approximation in arbitrary Clifford Algebra spaces. We…
- arXiv cs.AIresearchStealthRL: Reinforcement Learning Paraphrase Attacks for Multi-Detector Evasion of AI-Text Detectors
arXiv:2602.08934v3 Announce Type: replace-cross Abstract: AI-text detectors are increasingly used in high-stakes settings, but their robustness to meaning-preserving adversarial rewriting remains unclear. We introduce St…
- arXiv cs.AIresearchMitigating the Likelihood Paradox in Flow-based OOD Detection: An Entropic Perspective
arXiv:2602.09581v3 Announce Type: replace-cross Abstract: Deep generative models that can tractably compute input likelihoods, including normalizing flows, often assign unexpectedly high likelihoods to out-of-distributio…
- arXiv cs.AIresearchWhy Does Counterintuitive Likelihood Behavior Rarely Emerge in Tabular Anomaly Detection?
arXiv:2602.09593v3 Announce Type: replace-cross Abstract: Deep generative models with tractable likelihoods, exemplified by normalizing flows, offer an effective basis for anomaly detection through likelihood-based scori…
- arXiv cs.AIagentsContextual Memory Virtualisation: DAG-Based State Management and Structurally Lossless Trimming for LLM Agents
arXiv:2602.22402v2 Announce Type: replace-cross Abstract: As large language models engage in extended reasoning tasks, they accumulate significant state -- architectural mappings, trade-off decisions, codebase convention…
- arXiv cs.AIresearchCrimeNER: Curated Dataset and Methods for Research and Investigation in Language Intelligence
arXiv:2603.02150v3 Announce Type: replace-cross Abstract: The extraction of critical information from crime-related documents is a crucial task for law enforcement agencies. The extraction of this information can be inte…
- arXiv cs.AIresearchVORL-EXPLORE: A Hybrid Learning Planning Approach to Multi-Robot Exploration in Dynamic Environments
arXiv:2603.07973v2 Announce Type: replace-cross Abstract: Hierarchical multi-robot exploration decouples frontier allocation from local navigation, making systems brittle in dynamic environments. Without awareness of exe…
- arXiv cs.AIresearchMoE-SpAc: Efficient MoE Inference Based on Speculative Activation Utility in Heterogeneous Edge Scenarios
arXiv:2603.09983v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models enable scalable performance but face severe memory constraints on edge devices. Existing offloading strategies struggle with I/O b…
- arXiv cs.AIresearchMetaKE: Meta-Learning for Knowledge Editing Toward a Better Accuracy-Editability Trade-off
arXiv:2603.12677v4 Announce Type: replace-cross Abstract: Existing locate-then-edit Knowledge Editing (KE) methods typically decompose editing into two stages: upstream target representation optimization and downstream c…
- arXiv cs.AIagentsdaVinci-Env: Open SWE Environment Synthesis at Scale
arXiv:2603.13023v3 Announce Type: replace-cross Abstract: Training capable software engineering (SWE) agents demands large-scale, executable, and verifiable environments that provide dynamic feedback loops for iterative…