AI news archive.
19,854 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSpeakerMem-R1: Speaker-Centered Dual-Track Memory for Multi-Party Dialogue
arXiv:2609.26780v2 Announce Type: replace-cross Abstract: Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish who said…
- arXiv cs.AIresearchStable Marriage Problems with Ties and Incomplete Preferences: An Empirical Comparison of ASP, SAT, ILP, CP, and Local Search Methods
arXiv:2108.05165v3 Announce Type: replace Abstract: We study a variation of the Stable Marriage problem, where every man and every woman express their preferences as preference lists which may be incomplete and contain t…
- arXiv cs.AIresearchDecidable Reasoning About Time in Finite-Domain Situation Calculus Theories
arXiv:2402.03164v3 Announce Type: replace Abstract: Representing time is crucial for cyber-physical systems and has been studied extensively in the situation calculus. The most commonly used approach represents time by a…
- arXiv cs.AIagentsSmall Language Models are the Future of Agentic AI
arXiv:2506.02153v3 Announce Type: replace Abstract: Large language models (LLMs) are often praised for exhibiting near-human performance on a wide range of tasks and valued for their ability to hold a general conversatio…
- arXiv cs.AIresearchGlucose-ML: A collection of longitudinal diabetes datasets for development of robust AI solutions
arXiv:2507.14077v2 Announce Type: replace Abstract: Artificial intelligence (AI) algorithms are a critical part of state-of-the-art digital health technology for diabetes management. Yet, access to large high-quality dat…
- arXiv cs.AIagentsEndoCogniAgent: Closed-Loop Agentic Reasoning with Self-Consistency Validation for Endoscopic Diagnosis
arXiv:2508.07292v4 Announce Type: replace Abstract: Endoscopic diagnosis is an iterative process in which clinicians acquire, compare, and verify local visual evidence before reaching a conclusion. Current AI systems do…
- arXiv cs.AIresearchUltra Strong Machine Learning: LLM-Generated Explanations Do Not Yet Suffice for Teaching Humans Active Learning Strategy
arXiv:2509.00961v3 Announce Type: replace Abstract: Active learning is a general learning mechanism shared by artificial and human learners. Whether AI can teach humans such a strategy that transfers across domains is an…
- arXiv cs.AIresearchNavigating Taxonomic Expansions of Entity Sets Driven by Knowledge Bases
arXiv:2512.16953v3 Announce Type: replace Abstract: Recognizing similarities among entities is central to both human cognition and computational intelligence. Within this broader landscape, Entity Set Expansion is one pr…
- arXiv cs.AIagentsDistributed Legal Infrastructure for a Trustworthy Agentic Web
arXiv:2603.06884v2 Announce Type: replace Abstract: The agentic web marks a structural transition from a human-centered information network to a digital environment populated by artificial intelligence (AI) agents that p…
- arXiv cs.AIagentsAgentHazard: A Benchmark for Evaluating Harmful Behavior in Computer-Use Agents
arXiv:2604.02947v2 Announce Type: replace Abstract: Computer-use agents extend language models from text generation to persistent action over tools, files, and execution environments. Unlike chat systems, they maintain s…
- arXiv cs.AIagentsSAGE: A Self-Evolving Agentic Graph-Memory Engine for Structure-Aware Associative Memory
arXiv:2605.12061v2 Announce Type: replace Abstract: Long-term memory is becoming a central bottleneck for language agents. Exsting RAG and GraphRAG systems largely treat memory graphs as static retrieval middleware, whic…
- arXiv cs.AIresearchNIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol
arXiv:2605.15227v2 Announce Type: replace Abstract: Self-driving laboratories (SDLs) are attracting increasing attention as a means of accelerating scientific discovery; however, developing SDL software remains technical…
- arXiv cs.AIagentsAgent Memory: Characterization and System Implications of Stateful Long-Horizon Workloads
arXiv:2606.06448v2 Announce Type: replace Abstract: LLM agents are increasingly deployed on long-horizon tasks requiring sustained reasoning over extended interaction histories. Realizing this at scale requires agents to…
- arXiv cs.AIresearchExecution Realism and Reproducibility in LLM-Based Trading Systems: A Systematic Scoping Review and Evidence Audit
arXiv:2606.08285v3 Announce Type: replace Abstract: Execution realism remains weakly standardized in research on large-language-model-based trading systems, limiting comparison and reproduction across backtests, simulati…
- arXiv cs.AIagentsConfidence Composition for Multiagent Language Model Systems
arXiv:2606.13591v2 Announce Type: replace Abstract: Multiagent language model systems, such as collaborative reasoning and debate, produce multiple correlated candidate answers and confidence signals. However, these sign…
- arXiv cs.AIresearchAccelerating Disaggregated RL for Visual Generative LLMs with Diffusion-Based Parallelism and Trainer-Assisted Generation
arXiv:2606.24369v3 Announce Type: replace Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, driving the emergence of high-performance RL systems such as veRL for autoregressive large lan…
- arXiv cs.AIresearchEnhancing Fitness Intelligence through Domain-Specific LLM Post-Training
arXiv:2607.02118v2 Announce Type: replace Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Large Language Mode…
- arXiv cs.AIagentsSPINE: Bridging the Cyber-Physical Gap with Agentic AI
arXiv:2607.13049v2 Announce Type: replace Abstract: Foundation models give robots powerful high-level reasoning, yet turning that intelligence into reliable physical action remains difficult: roboticists must still align…
- arXiv cs.AIagentsSimulate to Generalize: Scaling Stateful Supervision for API-calling Agents using LLM World Models
arXiv:2607.16900v3 Announce Type: replace Abstract: Training agents that generalize to unseen, stateful environments requires a massive dataset of state-changing trajectories covering a vast and diverse set of APIs. Howe…
- arXiv cs.AIresearchVeriSimpl: Robust Optimization Modeling from Natural Language using Simplification-based Verification
arXiv:2607.20474v2 Announce Type: replace Abstract: Natural language interfaces can greatly benefit the accessibility and usability of optimization modeling, and recent advances in large language models (LLMs) show promi…
- arXiv cs.AIagentsDFAH-Bench: What Agreement Leaves Unmeasured in Financial Agents
arXiv:2607.20491v4 Announce Type: replace Abstract: When a financial agent repeats its decision, how much does that tell us about the actions behind it? DFAH-Bench examines this question through replay experiments, a con…
- arXiv cs.AIresearchWhere Does Neural Advantage Arise in Continuous-Time Dynamic Graph Prediction?
arXiv:2608.06765v3 Announce Type: replace Abstract: Aggregate performance on continuous-time dynamic graphs (CTDGs) combines, in a single score, the portion attributable to known temporal regularities and the additional…
- arXiv cs.AIresearchPTQ4SNN: Membrane-Aware Post-Training Quantization for Spiking Neural Networks
arXiv:2608.07066v2 Announce Type: replace Abstract: Spiking neural networks (SNNs) enable sparse and event-driven computation, but their low-bit deployment remains incomplete because recurrent membrane states are commonl…
- arXiv cs.AIagentsImproving Constraint Models with LLM Agents
arXiv:2608.08127v2 Announce Type: replace Abstract: The runtime of Constraint Programming (CP) solvers is highly sensitive to modeling choices, such as symmetry breaking, implied constraints, global constraints, constrai…
- arXiv cs.AIagentsBixBench3: Benchmarking AI agents on research-study-scale computational biology tasks
arXiv:2608.25286v2 Announce Type: replace Abstract: Artificial intelligence (AI) promises to accelerate biological research by automating computational analyses. Yet the ability of AI agents to execute on computational b…
- arXiv cs.AIresearchPerfReasoning: How Well Do LLMs Reason on Hardware Performance?
arXiv:2609.04476v3 Announce Type: replace Abstract: Performance modeling is central to hardware design and software optimization, yet constructing these models requires structured reasoning about computation, data reuse,…
- arXiv cs.AIagentsMARBO: Relational Belief Grounding for LLM Agents in Social Deduction Games
arXiv:2609.06563v2 Announce Type: replace Abstract: Social deduction games (SDGs) require agents to reason under partial observability by maintaining relational beliefs about hidden roles and team alignments. While recen…
- arXiv cs.AIagentsWhat Does Multi-Agent Debate Actually Change?
arXiv:2609.08016v3 Announce Type: replace Abstract: Multi-agent debate, in which several LLMs exchange arguments before producing an answer, raises a basic question: does expressed disagreement reflect changes in the mem…
- arXiv cs.AIresearchBenchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation
arXiv:2609.11115v4 Announce Type: replace Abstract: Benchmark researchers and developers of large language models (LLMs) and other AI systems need to find relevant evaluations, locate their benchmark datasets and code, a…
- arXiv cs.AIresearchPotential of Artificial Intelligence Algorithms for Identification of Relevant Diagnostic and Prognostic Biomarkers of Early-Stage Liver Cancer
arXiv:2609.15638v2 Announce Type: replace Abstract: This study explores the use of deep learning and explainable artificial intelligence to diagnose hepatocellular carcinoma (HCC) and define effective biomarkers across f…
- arXiv cs.AIresearchDA-Cramming: Enhancing Cost-Effective Language Model Pretraining with Dependency Agreement Integration
arXiv:2311.04799v3 Announce Type: replace-cross Abstract: Pretraining language models is still a challenge for many researchers due to its substantial computational costs. As such, there is growing interest in developing…
- arXiv cs.AIresearchHighway Congestion Reduction through Reinforcement Learning Based Eulerian Headway Control
arXiv:2412.02520v5 Announce Type: replace-cross Abstract: Connected automated vehicles (CAVs) equipped with adaptive cruise control (ACC) create new opportunities for highway congestion mitigation. Traditional practice r…
- arXiv cs.AIagentsELEMENT: Episodic and Lifelong Exploration via Maximum Entropy
arXiv:2412.03800v2 Announce Type: replace-cross Abstract: Reinforcement learning agents depend on reward signals whose density is rarely under the designer's control, and when such signals are absent, an agent must gener…
- arXiv cs.AIresearchFedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in Federated Learning
arXiv:2502.16396v2 Announce Type: replace-cross Abstract: Federated learning systems are increasingly threatened by data poisoning attacks, where malicious clients compromise global models by contributing tampered update…
- arXiv cs.AIresearchBigO(Bench): Can LLMs Generate Code with Controlled Time and Space Complexity?
arXiv:2503.15242v3 Announce Type: replace-cross Abstract: We introduce BigO(Bench), a novel coding benchmark designed to evaluate the capabilities of generative language models in understanding and generating code with s…
- arXiv cs.AIresearchAdaptive Helpfulness-Harmlessness Alignment with Preference Vectors
arXiv:2504.20106v4 Announce Type: replace-cross Abstract: Ensuring that large language models (LLMs) are both helpful and harmless is a critical challenge, as overly strict constraints can lead to excessive refusals, whi…
- arXiv cs.AIresearchTEMPURA: Temporal Event Masked Prediction and Understanding for Reasoning in Action
arXiv:2505.01583v2 Announce Type: replace-cross Abstract: Understanding causal event relationships and achieving fine-grained temporal grounding in videos remain challenging for vision-language models (VLMs). We propose…
- arXiv cs.AIresearchOV-MAP: Open-Vocabulary Zero-Shot 3D Instance Segmentation Map for Robots
arXiv:2506.11585v3 Announce Type: replace-cross Abstract: We introduce OV-MAP, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recognition capabilit…
- arXiv cs.AIagentsWebArxiv: A Reproducible Benchmark for Evaluating Multimodal Web Agents on arXiv Tasks
arXiv:2507.00938v4 Announce Type: replace-cross Abstract: Foundation models now enable autonomous agents to interact with real-world websites, but existing benchmarks emphasize general-purpose browsing, underrepresent re…
- arXiv cs.AIresearchTowards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint
arXiv:2508.20443v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained on massive datasets that may include private or copyrighted content. Due to growing privacy and ownership concerns, data…
- arXiv cs.AIagentsReal-time autonomous magnetic microrobot navigation across dynamic and biologically relevant environments
arXiv:2509.05500v2 Announce Type: replace-cross Abstract: Autonomous microrobots could enable minimally invasive interventions in confined biological environments, but their operation requires real-time navigation among…
- arXiv cs.AIresearchData Provenance Auditing of Fine-Tuned Large Language Models with a Text-Preserving Technique
arXiv:2510.09655v3 Announce Type: replace-cross Abstract: We propose a system for marking sensitive or copyrighted texts to detect their use in fine-tuning large language models under black-box access with statistical gu…
- arXiv cs.AIresearchProvable Anytime Ensemble Sampling Algorithms in Nonlinear Contextual Bandits
arXiv:2510.10730v3 Announce Type: replace-cross Abstract: We provide a unified algorithmic framework for ensemble sampling in nonlinear contextual bandits and develop corresponding regret bounds for two most common nonli…
- arXiv cs.AIagentsMulti-Agent Design Assistant for the Simulation of Inertial Fusion Energy
arXiv:2510.17830v3 Announce Type: replace-cross Abstract: Inertial fusion energy promises nearly unlimited, clean power if it can be achieved. However, the design and engineering of fusion systems requires controlling an…
- arXiv cs.AIresearchPOPI: Personalizing LLMs via Optimized Natural Language Preference Inference
arXiv:2510.17881v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are typically aligned with population-level preferences, despite substantial variation across individual users. We introduce POPI, a…
- arXiv cs.AIresearchMetamodel-Guided Model Generation with Layered Constraints
arXiv:2510.25890v4 Announce Type: replace-cross Abstract: Large language models (LLMs) enable natural-language interaction in engineering modeling, but generated models may violate structural constraints, domain rules, o…
- arXiv cs.AIresearchSTAR-VAE: A Scalable Latent-Variable Transformer for Controllable Molecular Generation
arXiv:2511.02769v2 Announce Type: replace-cross Abstract: Many molecular Transformers lack probabilistic latent variables for posterior inference and latent interpolation. We introduce STAR-VAE, a SELFIES-encoded, Transf…
- arXiv cs.AIresearchFinding Kissing Numbers with Game-theoretic Reinforcement Learning
arXiv:2511.13391v5 Announce Type: replace-cross Abstract: Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a central sphere has remaine…
- arXiv cs.AIresearchTowards Synergistic Teacher-AI Interactions with Generative Artificial Intelligence
arXiv:2511.19580v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is increasingly used in education, posing significant challenges for teachers adapting to these changes. GenAI offers u…
- arXiv cs.AIresearchRadiance-Field Guided Pretraining: Scaling Localization Models with Unlabeled Wireless Signals
arXiv:2512.07309v2 Announce Type: replace-cross Abstract: Radio frequency (RF)-based indoor localization offers significant promise for applications such as indoor navigation, augmented reality, and pervasive computing.…