AI news archive.
19,864 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchNARA: Anchor-Conditioned Representation Learning for Heterogeneous Vector Geoentities
arXiv:2605.12276v2 Announce Type: replace Abstract: Vector geospatial data represent the world as discrete geoentities, such as roads, buildings, and points of interest, each with semantic attributes, geometry, and spati…
- arXiv cs.AIresearchKGPFN: Unlocking the Potential of Knowledge Graph Foundation Model via In-Context Learning
arXiv:2605.14907v2 Announce Type: replace Abstract: Knowledge graph (KG) foundation models aim to generalize to graphs with unseen entities and relations by learning transferable relational structure. Most existing metho…
- arXiv cs.AIagentsOne Hypothesis Is Not Enough: Abductive Reasoning with Agentic Hypothesis Refinement over Knowledge Graphs
arXiv:2605.31370v2 Announce Type: replace Abstract: Abductive reasoning over knowledge graphs (KGs) seeks a first-order logic hypothesis whose answer set explains a given set of observed entities. Since many hypotheses c…
- arXiv cs.AIagentsCounterfactual Evidence Audits Predict LLM-Agent Susceptibility to Ranked Context
arXiv:2606.00914v2 Announce Type: replace Abstract: LLM agents increasingly decide from evidence assembled by upstream systems: retrievers choose documents, recommenders choose posts, and memory systems choose prior even…
- arXiv cs.AIresearchRethinking RAG in Long Videos: What to Retrieve and How to Use It?
arXiv:2606.13141v2 Announce Type: replace Abstract: Retrieval-augmented generation is extending beyond text to long videos, where query-relevant chunks can be represented across multiple modalities and temporal granulari…
- arXiv cs.AIresearchMental-R1: Aligning LLM Reasoning for Mental Health Assessment
arXiv:2606.13176v2 Announce Type: replace Abstract: Mental health problems such as anxiety, depression, and suicide remain urgent global challenges, where timely and accurate assessment is critical for effective interven…
- arXiv cs.AIagentsDissecting model behavior through agent trajectories
arXiv:2606.17454v3 Announce Type: replace Abstract: AI agent performance is not just a modeling problem, it is fundamentally a systems problem. The advanced capabilities of models are realized through agent harnesses. Th…
- arXiv cs.AIagentsLatent Goal Prediction from Language for Model-Based Planning
arXiv:2606.20627v3 Announce Type: replace Abstract: Joint-Embedding Predictive Architectures (JEPAs) enable agents to plan in latent space by imagining the outcomes of candidate actions, yet task specification remains a…
- arXiv cs.AIagentsSovereignPA-Bench: Evaluating User-Owned Personal Agents under Evolving Intent, Platform Mediation, and Consent Constraints
arXiv:2607.05363v2 Announce Type: replace Abstract: Personal agents that book and buy for their users act through platforms that rank, nudge, pre-select and collect data in their own interest. We introduce SovereignPA-Be…
- arXiv cs.AIresearchA Multi-Timescale Recursive Self-Improvement Engine for Open-Ended Persona Growth
arXiv:2607.08252v2 Announce Type: replace Abstract: Role-playing AI personas today do not grow: they hold a fixed character, so the relationship a user builds with them has nothing to accumulate on. We introduce AutoPers…
- arXiv cs.AIagentsRethinking the Evaluation of Harness Evolution for Agents
arXiv:2607.12227v4 Announce Type: replace Abstract: Harness evolution is an iterative search procedure that repeatedly evaluates and revises candidate harnesses used for LLM agents using task feedback. We revisit the eva…
- arXiv cs.AIresearchHow Artificial Intelligence LLM Engines Shape the Global Conflict Information Environment
arXiv:2607.14197v2 Announce Type: replace Abstract: Artificial Intelligence (AI) answer engines now field a growing share of the questions that analysts, scholars, and the public ask about issues of peace and conflict. L…
- arXiv cs.AIagentsWorld Action Planner: Generalizable Robot Decision-Making with Action-Conditioned World Models
arXiv:2607.27599v2 Announce Type: replace Abstract: Building generalizable robot agents for diverse applications remains a fundamental challenge. While imitation learning-based policies can perform well in familiar train…
- arXiv cs.AIresearchWAM-OPD: Joint Video-Action Supervision for World Action Model Post-Training with On-Policy Distillation
arXiv:2608.22364v2 Announce Type: replace Abstract: World Action Models (WAMs) generate both future video and robot actions, offering two connected outputs for post-training supervision. How can a pretrained WAM learn fr…
- arXiv cs.AIagentsWill the User Ever Know? Covert Indirect Prompt Injection Attacks on Tool-Using LLM Agents
arXiv:2608.30362v3 Announce Type: replace Abstract: As LLM agents take real-world actions through tools, indirect prompt injection (IPI) has emerged as a serious threat. The standard metric, Attack Success Rate (ASR), co…
- arXiv cs.AIresearchLearning transferable human physiology from two million hours of sleep with SleepFM-2
arXiv:2609.06849v2 Announce Type: replace Abstract: Sleep provides a nightly window into health by capturing coordinated activity across the brain, heart, muscles and respiratory system. We introduce SleepFM-2, a sleep f…
- arXiv cs.AIagentsBusMA: A Bus Communication Substrate for Multi-Agent Systems
arXiv:2609.15054v2 Announce Type: replace Abstract: Multi-Agent (MA) systems are effective at solving complex tasks that demand planning, tool use, and the synthesis of evidence from multiple sources. Existing systems ty…
- arXiv cs.AIresearchLearning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotion
arXiv:2209.14887v3 Announce Type: replace-cross Abstract: Robotic locomotion is often approached with the goal of maximizing robustness and reactivity by increasing motion control frequency. We challenge this intuitive n…
- arXiv cs.AIresearchVIDiff: Translating Videos via Multi-Modal Instructions with Diffusion Models
arXiv:2311.18837v2 Announce Type: replace-cross Abstract: Diffusion models have achieved significant success in image and video generation. This motivates a growing interest in video editing tasks, where videos are edite…
- arXiv cs.AIresearchTowards Unified Music Emotion Recognition across Dimensional and Categorical Models
arXiv:2502.03979v3 Announce Type: replace-cross Abstract: One of the most significant challenges in Music Emotion Recognition (MER) comes from the fact that emotion labels can be heterogeneous across datasets with regard…
- arXiv cs.AIresearchHybrid Reasoning Systems That Prioritize and Enhance Human Intelligence
arXiv:2504.13477v3 Announce Type: replace-cross Abstract: In a world of accelerating change, there is a need for wise and adaptive human reasoning. Integrating AI capabilities with human guidance offers promise, though h…
- arXiv cs.AIresearchVTBench: Evaluating Visual Tokenizers for Autoregressive Image Generation
arXiv:2505.13439v2 Announce Type: replace-cross Abstract: Autoregressive (AR) models have recently shown strong performance in image generation, where a critical component is the visual tokenizer (VT) that maps continuou…
- arXiv cs.AIresearchEvaluating the Retrieval Robustness of Large Language Models
arXiv:2505.21870v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) generally enhances large language models' (LLMs) ability to solve knowledge-intensive tasks. But RAG could also lead to perfo…
- arXiv cs.AIresearchRobust Adversarial Quantification via Conflict-Aware Evidential Deep Learning
arXiv:2506.05937v3 Announce Type: replace-cross Abstract: Reliability of deep learning models is critical for deployment in high-stakes applications, where out-of-distribution or adversarial inputs may lead to detrimenta…
- arXiv cs.AIresearchMitigating Watermark Forgery in Generative Models via Randomized Key Selection
arXiv:2507.07871v5 Announce Type: replace-cross Abstract: Watermarking enables GenAI providers to verify whether content was generated by their models. A watermark is a hidden signal in the content, whose presence can be…
- arXiv cs.AIresearchMultimodal Representation Learning Conditioned on Semantic Relations
arXiv:2508.17497v3 Announce Type: replace-cross Abstract: Multimodal representation learning has been largely driven by contrastive models such as CLIP, which learn a shared embedding space by aligning paired image-text…
- arXiv cs.AIresearchEEGDM: Learning EEG Representation with Latent Diffusion Model
arXiv:2508.20705v5 Announce Type: replace-cross Abstract: Recent advances in self-supervised learning for EEG representation have largely relied on masked reconstruction, where models are trained to recover randomly mask…
- arXiv cs.AIresearchCocoon: A System Architecture for Differentially Private Training with Correlated Noises
arXiv:2510.07304v2 Announce Type: replace-cross Abstract: Machine learning (ML) models memorize and leak training data, causing serious privacy issues to data owners. Training algorithms with differential privacy (DP) ha…
- arXiv cs.AIagentsLLM-Guided Reinforcement Learning with Representative Agents for Traffic Modeling
arXiv:2511.06260v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as behavioral proxies for self-interested travelers in agent-based traffic models. Although more flexible and g…
- arXiv cs.AIresearchA Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News
arXiv:2511.18618v2 Announce Type: replace-cross Abstract: In our daily lives, newspapers are an essential information source that impacts how the public talks about present-day issues. However, effectively navigating the…
- arXiv cs.AIresearchScience Is Falling Behind the Frontier: Foundation Model Adoption Across Half a Million Papers
arXiv:2511.21739v2 Announce Type: replace-cross Abstract: We present the first large-scale analysis of AI foundation model usage in science -- not just citations or keywords. We find that adoption has grown rapidly, at n…
- arXiv cs.AIresearchDemystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling
arXiv:2512.19905v3 Announce Type: replace-cross Abstract: Recent developments in large language models have shown advantages in reallocating a notable share of computational resource from training time to inference time.…
- arXiv cs.AIresearchMorality is Contextual: Learning Interpretable Moral Contexts from Human Data with Probabilistic Clustering and Large Language Models
arXiv:2512.21439v2 Announce Type: replace-cross Abstract: A key question in current AI alignment research is how to make AI algorithms learn moral values. Because human morality is highly context-dependent, actions are j…
- arXiv cs.AIagentsRecoverability Has a Law: The ERR Measure for Tool-Augmented Agents
arXiv:2601.22352v2 Announce Type: replace-cross Abstract: Language model agents often appear capable of self-recovery after failing tool call executions, yet this behavior lacks a formal explanation. We present a predict…
- arXiv cs.AIresearchExtended to Reality: Prompt Injection in 3D Environments
arXiv:2602.07104v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have advanced the capabilities to interpret and act on visual input in 3D environments, empowering diverse applications s…
- arXiv cs.AIresearchANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling
arXiv:2602.09009v4 Announce Type: replace-cross Abstract: Scaling network depth has been a central driver behind the success of modern foundation models, yet recent investigations suggest that deep layers are often under…
- arXiv cs.AIresearchThe Effective Depth Paradox: Topology and Trainability in Deep CNNs
arXiv:2602.13298v4 Announce Type: replace-cross Abstract: This paper presents a controlled comparative study of convolutional neural network (CNN) topology and image classification performance across the architectural fa…
- arXiv cs.AIresearchGoldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning
arXiv:2602.14868v3 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful paradigm for unlocking reasoning capabilities in language models. However, relying on sparse rewards makes this p…
- arXiv cs.AIresearchSensory-Aware Sequential Recommendation via Review-Distilled Representations
arXiv:2603.02709v4 Announce Type: replace-cross Abstract: Sequential recommenders learn behavioral patterns from item identifiers, while the experiential properties that users describe in reviews, such as how products lo…
- arXiv cs.AIresearchEvaluation format, not only model capability, shapes measured triage failure in consumer health AI
arXiv:2603.11413v5 Announce Type: replace-cross Abstract: A recent Nature Medicine study reported that ChatGPT Health under-triages 51.6% of emergencies and concluded that consumer-facing AI triage poses safety risks. It…
- arXiv cs.AIresearchControllable Accent Normalization via Discrete Diffusion
arXiv:2603.14275v3 Announce Type: replace-cross Abstract: Existing accent normalization methods do not typically offer control over accent strength, yet many applications-such as language learning and dubbing-require tun…
- arXiv cs.AIresearchExploring Subnetwork Interactions in Heterogeneous Brain Network via Prior-Informed Graph Learning
arXiv:2603.19307v2 Announce Type: replace-cross Abstract: Modeling the complex interactions among functional subnetworks is crucial for the diagnosis of mental disorders and the identification of functional pathways. How…
- arXiv cs.AIresearchSpectral Alignment in Forward-Backward Representations via Temporal Abstraction
arXiv:2603.20103v4 Announce Type: replace-cross Abstract: Forward-backward (FB) representations provide a powerful framework for learning the successor representation (SR) in continuous spaces by enforcing a low-rank fac…
- arXiv cs.AIresearchMany Preferences, Few Policies: Compact Portfolios for Multi-Objective LLM Alignment
arXiv:2604.04144v3 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) requires balancing competing objectives such as helpfulness, harmlessness, and conciseness. The appropriate balance varies a…
- arXiv cs.AIresearchIs a Picture Worth a Thousand Words? Adaptive Multimodal Fact-Checking with Visual Evidence Necessity
arXiv:2604.04692v3 Announce Type: replace-cross Abstract: Automated fact-checking is a crucial task that supports a responsible information ecosystem. While recent research has progressed from text-only to multimodal fac…
- arXiv cs.AIagentsVerify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis
arXiv:2604.10800v2 Announce Type: replace-cross Abstract: Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified conclusions, and…
- arXiv cs.AIresearchRhetorical Questions in LLM Representations: A Linear Probing Study
arXiv:2604.14128v3 Announce Type: replace-cross Abstract: Rhetorical questions are asked not to seek information but to persuade or signal stance. How large language models internally represent them remains unclear. We a…
- arXiv cs.AIagentsHow Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks
arXiv:2604.22750v3 Announce Type: replace-cross Abstract: The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that require a signi…
- arXiv cs.AIagentsWho Guards the Benchmarks? Automated Auditing of LLM Agent Benchmarks
arXiv:2604.24955v2 Announce Type: replace-cross Abstract: As benchmarks grow in complexity, many apparent agent failures are not failures of the agent at all---they are failures of the benchmark itself: broken specificat…
- arXiv cs.AIresearchDual Certified White-Box Inference for Input Convex Neural Networks
arXiv:2605.04722v2 Announce Type: replace-cross Abstract: Input convex neural networks (ICNNs) are used to learn convex objectives whose minimizers define decisions, making efficient and reliable optimization central to…