AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchEfficient Hierarchical Transformers for Representing Log Data
arXiv:2408.16803v2 Announce Type: replace-cross Abstract: Transformers have gained widespread acclaim for their versatility in handling diverse data structures, yet their application to log data remains underexplored. Lo…
- arXiv cs.AIresearchHardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
arXiv:2409.18778v2 Announce Type: replace-cross Abstract: Efficiently determining the satisfiability of a boolean equation -- known as the SAT problem for brevity -- is crucial in various industrial problems. Recently, t…
- arXiv cs.AIresearchScrew Geometry Meets Bandits: Incremental Acquisition of Demonstrations to Generate Manipulation Plans
arXiv:2410.18275v2 Announce Type: replace-cross Abstract: In this paper, we study the problem of methodically obtaining a sufficient set of kinesthetic demonstrations, one at a time, such that a robot can be confident of…
- arXiv cs.AIresearchMoFlow: One-Step Flow Matching for Human Trajectory Forecasting via Implicit Maximum Likelihood Estimation based Distillation
arXiv:2503.09950v2 Announce Type: replace-cross Abstract: In this paper, we address the problem of human trajectory forecasting, which aims to predict the inherently multi-modal future movements of humans based on their…
- arXiv cs.AIresearch1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
arXiv:2503.14858v5 Announce Type: replace-cross Abstract: Scaling up self-supervised learning has driven breakthroughs in language and vision, yet comparable progress has remained elusive in reinforcement learning (RL).…
- arXiv cs.AIresearchOptimizing Breast Cancer Detection in Mammograms: A Comprehensive Study of Transfer Learning, Resolution Reduction, and Multi-View Classification
arXiv:2503.19945v4 Announce Type: replace-cross Abstract: Mammography, an X-ray-based imaging technique, remains central to the early detection of breast cancer. Recent advances in artificial intelligence have enabled in…
- arXiv cs.AIresearchRobotic Long-Horizon Manipulation with Progressive In-Context Code Generation and Episodic Feedback
arXiv:2503.21969v4 Announce Type: replace-cross Abstract: Robotic long-horizon manipulation requires robots to compose perception, reasoning, and action over extended task sequences, yet existing language-conditioned fra…
- arXiv cs.AIresearchRobotic Long-Horizon Manipulation with Bayesian Non-parametric Skill Priors
arXiv:2503.21975v2 Announce Type: replace-cross Abstract: Long-horizon manipulation under sparse rewards remains challenging for reinforcement learning due to delayed feedback and inefficient exploration. Existing skill-…
- arXiv cs.AIresearchErased but Not Forgotten: How Backdoors Compromise Concept Erasure
arXiv:2504.21072v4 Announce Type: replace-cross Abstract: The expansion of text-to-image diffusion models has raised concerns about harmful outputs, from fabricated depictions of public figures to sexually explicit image…
- arXiv cs.AIagentsA Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI
arXiv:2505.01458v3 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, time-consuming, and un…
- arXiv cs.AIresearchGraph-Based Floor Separation Using Node Embeddings and Clustering of WiFi Trajectories
arXiv:2505.08088v5 Announce Type: replace-cross Abstract: Indoor positioning systems (IPSs) are increasingly vital for location-based services in complex multi-storey environments. This study proposes a novel graph-based…
- arXiv cs.AIresearchUsing Echo-State Networks to Reproduce Rare Events in Chaotic Systems
arXiv:2505.16208v3 Announce Type: replace-cross Abstract: Echo-State Networks (ESNs) are known to reproduce trajectories and main properties of chaotic attractors. Here, we investigate the question of whether ESNs can re…
- arXiv cs.AIresearchAnomaly Detection and Generation with Diffusion Models: A Survey
arXiv:2506.09368v2 Announce Type: replace-cross Abstract: Anomaly detection (AD) plays a pivotal role across diverse domains, including cybersecurity, finance, healthcare, and industrial manufacturing, by identifying une…
- arXiv cs.AIresearchEduAlign: Aligning Educational LLMs for Helpfulness, Personalization, and Creativity
arXiv:2507.20335v2 Announce Type: replace-cross Abstract: Educational language models should pursue three complementary objectives: helpfulness through responsible guidance, personalization to learner needs, and creativi…
- arXiv cs.AIresearchOCSVM-Guided Representation Learning for Unsupervised Anomaly Detection
arXiv:2507.21164v3 Announce Type: replace-cross Abstract: Unsupervised anomaly detection (UAD) aims to detect anomalies without labeled data, a necessity in many machine learning applications where anomalous samples are…
- arXiv cs.AIagentsResource-Limited Joint Multimodal Sentiment Reasoning and Classification via Chain-of-Thought Enhancement and Distillation
arXiv:2508.05234v2 Announce Type: replace-cross Abstract: Current approaches for Multimodal Sentiment Analysis (MSA) primarily leverage the knowledge and reasoning capabilities of parameter-heavy (Multimodal) LLMs for cl…
- arXiv cs.AIresearchEnhancing Knowledge Tracing through Leakage-Free and Recency-Aware Embeddings
arXiv:2508.17092v3 Announce Type: replace-cross Abstract: Knowledge Tracing (KT) aims to predict a student's future performance based on their sequence of interactions with learning content. Many KT models rely on knowle…
- arXiv cs.AIagentsZeST: A VLM-based Zero-Shot Traversability Navigation for Unknown Environments
arXiv:2508.19131v4 Announce Type: replace-cross Abstract: Advances in robotics and autonomous navigation systems hinge on the ability to predict terrain traversability accurately. Traditional methods for generating datas…
- arXiv cs.AIagentsCOCORELI: Enforcing Execution Preconditions for Reliable Collaborative Instruction Following
arXiv:2509.04470v3 Announce Type: replace-cross Abstract: Autonomous agents executing human instructions must operate reliably even when instructions are incomplete. While recent approaches improve detection of missing i…
- arXiv cs.AIresearchPhysics-informed GNN for medium-high voltage AC power flow with edge-aware attention and line search correction operator
arXiv:2509.22458v3 Announce Type: replace-cross Abstract: Physics-informed graph neural networks (PIGNNs) have emerged as fast AC power-flow solvers that can replace the classic NewtonRaphson (NR) solvers, especially whe…
- arXiv cs.AIresearchPATCH: Learnable Tile-level Hybrid Sparsity for LLMs
arXiv:2509.23410v5 Announce Type: replace-cross Abstract: Large language models (LLMs) deliver impressive performance but incur prohibitive memory and compute costs at deployment. Model pruning is an effective way to red…
- arXiv cs.AIresearchReinforcement Learning with Verifiable yet Noisy Rewards under Imperfect Verifiers
arXiv:2510.00915v5 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) replaces costly human labeling with automated verifiers. To reduce verifier hacking, many RLVR systems binar…
- arXiv cs.AIresearchNeural Bayesian Filtering
arXiv:2510.03614v2 Announce Type: replace-cross Abstract: Sequential estimation under partial observability requires tracking beliefs that may be high-dimensional, multimodal, and non-Gaussian. Classical Bayesian filters…
- arXiv cs.AIresearchInverse Mixed-Integer Programming: Learning Constraints then Objective Functions
arXiv:2510.04455v3 Announce Type: replace-cross Abstract: Data-driven inverse optimization for mixed-integer linear programs (MILPs), which seeks to learn an objective function and constraints consistent with observed de…
- arXiv cs.AIagentsFreshBrew: A Benchmark for Evaluating AI Agents on Java Code Migration
arXiv:2510.04852v3 Announce Type: replace-cross Abstract: AI coding assistants are rapidly becoming integral to modern software development. A key challenge in this space is the continual need to migrate and modernize co…
- arXiv cs.AIresearchDemystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think?
arXiv:2510.12680v2 Announce Type: replace-cross Abstract: Hybrid thinking enables LLMs to switch between reasoning and direct answering, offering a balance between efficiency and reasoning capability. Yet our experiments…
- arXiv cs.AIresearchMCA: Modality Composition Awareness for Robust Composed Multimodal Retrieval
arXiv:2510.15543v2 Announce Type: replace-cross Abstract: Multimodal retrieval, which seeks to retrieve relevant content across modalities such as text or image, supports applications from AI search to contents productio…
- arXiv cs.AIresearchA Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning
arXiv:2510.18814v5 Announce Type: replace-cross Abstract: Can a language model improve reasoning by learning from its own imperfect responses, without rewards or teacher-provided solutions? We present Self-evolving Post-…
- arXiv cs.AIresearchLearning Granger Causality under Latent Confounding via Intervention-Induced Heterogeneity
arXiv:2510.19138v2 Announce Type: replace-cross Abstract: Granger causality characterizes directed predictive dependencies in multivariate time series, but recovering such dependencies becomes challenging in the presence…
- arXiv cs.AIagentsUser Misconceptions of LLM-Based Conversational Programming Assistants
arXiv:2510.25662v3 Announce Type: replace-cross Abstract: Programming assistants powered by large language models (LLMs) have become widely available, with conversational assistants such as ChatGPT particularly accessibl…
- arXiv cs.AIresearchMedForj: An open, large-scale foundational generative prior for high-resolution 3D brain MRI
arXiv:2510.26834v2 Announce Type: replace-cross Abstract: This work introduces MedForj, a suite of 3D foundational generative priors based on diffusion models. The MedForj models were trained on $72{,}659$ 1~mm isotropic…
- arXiv cs.AIresearchOolong: Evaluating Long Context Reasoning and Aggregation Capabilities
arXiv:2511.02817v2 Announce Type: replace-cross Abstract: As model context lengths continue to grow, concerns about whether models effectively use the full context length have persisted. While several carefully designed…
- arXiv cs.AIresearchDeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
arXiv:2511.04086v2 Announce Type: replace-cross Abstract: With the rapid growth of graph-structured data in critical domains, unsupervised graph-level anomaly detection (UGAD) has become a pivotal task. UGAD seeks to ide…
- arXiv cs.AIresearchProDER: A Continual Learning Approach for Fault Classification and Localization in Evolving Smart Grids
arXiv:2511.05420v4 Announce Type: replace-cross Abstract: Data-driven fault diagnosis models for smart grids are usually trained once on a fixed dataset, whereas in operation new fault types appear and monitoring is exte…
- arXiv cs.AIagentsScalable Decision Making for Games of Imperfect Information
arXiv:2511.07312v2 Announce Type: replace-cross Abstract: Real-world decision-making generally involves hidden information, that is, information that is unknown to one agent but possessed by another. Unfortunately, the p…
- arXiv cs.AIresearchGlobal Optimization on Graph-Structured Data via Gaussian Processes with Spectral Representations
arXiv:2511.07734v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) is a powerful framework for optimizing expensive black-box objectives, yet extending it to graph-structured domains remains challenging…
- arXiv cs.AIresearchBi-objective chance-constrained evolutionary optimization for large-scale open-pit mine scheduling under geological uncertainty
arXiv:2511.08275v2 Announce Type: replace-cross Abstract: The open-pit mine scheduling problem (OPMSP) is a complex optimization problem in long-term mine planning that involves numerous operational and geological constr…
- arXiv cs.AIresearchEulerESG: Automating ESG Disclosure Analysis with LLMs
arXiv:2511.21712v2 Announce Type: replace-cross Abstract: Environmental, Social, and Governance (ESG) reports have become central to how companies communicate climate risk, social impact, and governance practices, yet th…
- arXiv cs.AIagentsHierarchical Decentralized Multi-Agent Coordination with Privacy-Preserving Knowledge Sharing: Extending AgentNet for Scalable Autonomous Systems
arXiv:2512.00614v2 Announce Type: replace-cross Abstract: Decentralized multi-agent systems have shown promise in enabling autonomous collaboration among LLM-based agents. While AgentNet demonstrated the feasibility of f…
- arXiv cs.AIresearchMixed Data Clustering Survey and Challenges
arXiv:2512.03070v3 Announce Type: replace-cross Abstract: The advent of the big data paradigm has transformed how industries manage and analyze information, ushering in an era of unprecedented data volume, velocity, and…
- arXiv cs.AIresearchThe Universal Weight Subspace Hypothesis
arXiv:2512.05117v3 Announce Type: replace-cross Abstract: We show that deep neural networks trained across diverse tasks exhibit remarkably similar low-dimensional parametric subspaces. We provide the first large-scale e…
- arXiv cs.AIresearchTowards Optimal Valve Prescription for Transcatheter Aortic Valve Replacement (TAVR) Surgery: A Machine Learning Approach
arXiv:2512.09198v2 Announce Type: replace-cross Abstract: Transcatheter Aortic Valve Replacement (TAVR) has emerged as a prominent, minimally invasive treatment for patients with severe aortic stenosis, a life-threatenin…
- arXiv cs.AIresearchContrastive Time Series Forecasting with Anomalies
arXiv:2512.11526v2 Announce Type: replace-cross Abstract: Time series forecasting predicts future values from past data. In real-world settings, some anomalous events have lasting effects and influence the forecast, whil…
- arXiv cs.AIresearchMemory as Resonance: A Biomimetic Architecture for Infinite Context Memory on Ergodic Phonetic Manifolds
arXiv:2512.20245v2 Announce Type: replace-cross Abstract: The memory of contemporary Large Language Models is bound by a physical paradox: as they learn, they fill up. The linear accumulation (O(N)) of Key-Value states t…
- arXiv cs.AIresearchSymphonym: Universal Phonetic Embeddings for Cross-Script Toponym Matching
arXiv:2601.06932v5 Announce Type: replace-cross Abstract: Matching place names across writing systems is a persistent obstacle to integrating multilingual geographic sources, from modern gazetteers to medieval itinerarie…
- arXiv cs.AIagentsATOD: An Evaluation Framework and Benchmark for Agentic Task-Oriented Dialogue Systems
arXiv:2601.11854v3 Announce Type: replace-cross Abstract: Agentic task-oriented dialogue (TOD) requires systems to track concurrent goals, dependencies, and long-horizon state. We examine goal-lifecycle recovery from fix…
- arXiv cs.AIresearchVulnerability of LLMs' Stated Beliefs? LLMs Belief Resistance Check Through Strategic Persuasive Conversation Interventions
arXiv:2601.13590v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly employed in various question-answering tasks. However, recent studies showcase that LLMs are susceptible to persuasi…
- arXiv cs.AIresearchFlashMoE: Reducing SSD I/O Bottlenecks via ML-Based Cache Replacement for Mixture-of-Experts Inference on Edge Devices
arXiv:2601.17063v2 Announce Type: replace-cross Abstract: Recently, Mixture-of-Experts (MoE) models have gained attention for efficiently scaling large language models. Although these models are extremely large, their sp…
- arXiv cs.AIresearchDe-occluding broadband metalens
arXiv:2601.19403v2 Announce Type: replace-cross Abstract: Obstructions such as raindrops, fences, or dust degrade captured images, especially when mechanical cleaning is infeasible. Conventional solutions to obstructions…
- arXiv cs.AIresearchRouting-Aware Safety Alignment for Mixture-of-Experts Models
arXiv:2602.04448v4 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) language models introduce unique challenges for safety alignment due to their sparse routing mechanisms, which can enable degenerate opti…