AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchAsking a Multimodal LLM Whether Someone Fell: Zero-Shot Screening of Low-Resolution Thermal Video in a Laboratory and an Occupied Home
arXiv:2610.29913v1 Announce Type: cross Abstract: Thermal cameras can watch over older people living alone without capturing faces, and multimodal large language models (LLMs) can judge a short video without task-specifi…
- arXiv cs.AIresearchUnintended Side Effects of Value Training in LLMs
arXiv:2610.29922v1 Announce Type: cross Abstract: As LLMs are increasingly deployed in value-sensitive contexts, aligning them with human values has emerged as a post-training objective in NLP, aimed at instilling additi…
- arXiv cs.AIresearchPrivacy in Context Is Being Overlooked in the Age of General-Purpose LLMs
arXiv:2610.29925v1 Announce Type: cross Abstract: As large language models (LLMs) continue to grow in scope and capability, privacy concerns are on the rise. Since users increasingly interact with a single general-purpos…
- arXiv cs.AIresearchYour Benchmark Is an Empirical Measure Over Difficulty
arXiv:2610.29927v1 Announce Type: cross Abstract: A benchmark is not merely a collection of test questions; it naturally induces an empirical measure over difficulty. In this work, we develop this measure-based view of b…
- arXiv cs.AIresearchGraph Topology Meets Energy-Driven Pathfinding: Preserving Contextual Consistency in Retrieval-Augmented Generation
arXiv:2610.29933v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) frequently integrates knowledge graphs (KGs) for complex multi-hop question answering. However, their performance is increasingly bot…
- arXiv cs.AIresearchCulturalRiddles: A Multicultural Benchmark of Riddles
arXiv:2610.29968v3 Announce Type: replace-cross Abstract: As LLMs expand their language coverage, evaluating how well they understand and represent diverse cultures becomes increasingly important. However, many benchmark…
- arXiv cs.AIresearchHiddenLens: A Multi-Layer LLM Framework for Detecting and Resolving Hidden Assumptions in Software Requirements
arXiv:2610.29996v1 Announce Type: cross Abstract: Natural-language software requirements often omit assumptions about performance, operating conditions, user behaviour, and domain constraints, affecting architecture, tes…
- arXiv cs.AIresearchEvery Alarm Has a Cause: An Open Generator of Telecom Alarm Storms with Exact Root Causes, Bound to NORIA-O, RFC 8632 and TMF642
arXiv:2610.30004v1 Announce Type: cross Abstract: Alarm root-cause analysis is studied on data that cannot be shared. Operator logs are confidential, so what the field publishes is a causal graph between alarm types rath…
- arXiv cs.AIresearchBuilding Auditable AI Text Detectors with Sparse Autoencoders
arXiv:2610.30006v1 Announce Type: cross Abstract: AI-generated text detectors are increasingly deployed in consequential settings---peer review, education, admissions, journalism, and content moderation---where their out…
- arXiv cs.AIresearchCode Comprehensor: Hierarchical Documentation and Cross-Modal Retrieval for Large Repositories
arXiv:2610.30016v2 Announce Type: replace-cross Abstract: Understanding large, complex, and rapidly evolving code bases remains a core challenge for software engineering at scale, hindering onboarding, maintenance, refac…
- arXiv cs.AIresearchStationarity Constraints Improve Both Energies and Densities of Machine-Learned Exchange-Correlation Functionals
arXiv:2610.30022v1 Announce Type: cross Abstract: Empirical exchange-correlation functionals are fitted on fixed orbitals but used self-consistently, so better energies often come with worse densities. We show that the B…
- arXiv cs.AIresearchSP-HLM: Sparse-Pose-Driven Motion Generation and Whole-Body Control for Humanoid Loco-Manipulation
arXiv:2610.30044v1 Announce Type: cross Abstract: Humanoid loco-manipulation requires an effective interface between high-level task policies and whole-body control. Existing interfaces typically rely on a single action…
- arXiv cs.AIresearchFrom Reasoning to Action: Benchmarking Frontier AI Models on LIBERO-10 Robot Manipulation Tasks
arXiv:2610.30051v1 Announce Type: cross Abstract: Recent advances in frontier AI models have demonstrated remarkable capabilities in visual understanding, reasoning, planning, and tool use, raising the possibility of usi…
- arXiv cs.AIresearchAtomicRL: Atomic Reinforcement Learning for Long-Horizon Robotic Manipulation
arXiv:2610.30097v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have shown promise in robotic manipulation, but imitation learning (IL) alone often struggles to master complex long-horizon skills. R…
- arXiv cs.AIresearchDifferentially Private Sparse Reward Estimation with Preference Feedback
arXiv:2610.30099v1 Announce Type: cross Abstract: Reinforcement Learning with Human Feedback (RLHF) has become a central paradigm for aligning Large Language Models with human values. However, the reliance on sensitive p…
- arXiv cs.AIresearchBatchBench: Benchmarking AI Robustness to Batch Effects and Domain Shift in Biomedical Images - A JUMP Cell Painting Leaderboard
arXiv:2610.30104v1 Announce Type: cross Abstract: Despite recent advances, current AI systems remain highly susceptible to domain shifts, particularly in biomedical imaging, where images are usually acquired under substa…
- arXiv cs.AIresearchThe End of Consensus Research?
arXiv:2610.30114v1 Announce Type: cross Abstract: Consensus is a fundamental problem in distributed computing and at the core of state machine replication (SMR). Despite decades of active human research, discovering prac…
- arXiv cs.AIresearchEnvironment Duels: A Microcosm of LLM Co-Evolution
arXiv:2610.30116v1 Announce Type: cross Abstract: Through a tangle of real-world interactions, from synthetic training pipelines to data shared on the open web, frontier LLMs absorb what their predecessors and competitor…
- arXiv cs.AIresearchPhysiCalWorld: In-Context Physics Calibration for World Models
arXiv:2610.30125v1 Announce Type: cross Abstract: Existing world models typically perceive a scene through current visual frame or a narrow history window. However, these observations may not reveal the physics propertie…
- arXiv cs.AIresearchThink Harder Where It Matters: Item-Level Adaptive Recursion for Sequential Recommendation
arXiv:2610.30128v1 Announce Type: cross Abstract: Existing sequential recommenders usually allocate a fixed computational budget to every item in a user's interaction history, regardless of the item's contribution to the…
- arXiv cs.AIresearchGenerative Artificial Intelligence for Internet of Things Computing: A Systematic Survey
arXiv:2504.07635v2 Announce Type: replace Abstract: The integration of Generative Artificial Intelligence (GenAI) within the Internet of Things (IoT) is garnering considerable interest. This growing attention stems from…
- arXiv cs.AIresearchPRISM: Prompt-Refined In-Context System Modelling for Financial Retrieval
arXiv:2511.14130v3 Announce Type: replace Abstract: Deploying LLMs for financial information retrieval demands accuracy, cost efficiency, and reproducibility, yet most approaches require expensive fine-tuning. PRISM is a…
- arXiv cs.AIresearchSynthesis and Verification of Register Automata over Data Sequences (Technical Report)
arXiv:2511.19100v2 Announce Type: replace Abstract: Data sequences, such as time series, traces, and sensor streams, are words over large or infinite data domains. Their properties often depend on comparisons between val…
- arXiv cs.AIresearchA Theoretical Analysis of Why Masked Diffusion Models Mitigate the Reversal Curse
arXiv:2602.02133v3 Announce Type: replace Abstract: Autoregressive language models (ARMs) suffer from the reversal curse: after learning ''$A$ is $B$,'' they often fail on the reverse query ''$B$ is $A$.'' Masked diffusi…
- arXiv cs.AIresearchThe Alien Space of Science: Sampling Coherent but Cognitively Unavailable Research Directions
arXiv:2603.01092v3 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to researchers. Many directions are coherent in light of the literatu…
- arXiv cs.AIresearchFactReview: Evidence-Grounded Peer Review with Execution-Based Claim Verification
arXiv:2604.04074v5 Announce Type: replace Abstract: AI is accelerating scientific research, but providing timely and trustworthy feedback remains challenging. Such feedback requires evaluating specific claims against ver…
- arXiv cs.AIresearchAdaptive auditing of AI systems with anytime-valid guarantees
arXiv:2605.07002v2 Announce Type: replace Abstract: A major bottleneck in characterizing the failure modes of generative AI systems is the cost and time of annotation and evaluation. Consequently, adaptive testing paradi…
- arXiv cs.AIresearchWindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain
arXiv:2605.09511v2 Announce Type: replace Abstract: Many decisions in complex terrain require fast wind estimates at specific locations and heights rather than dense forecasts on fixed grids. We present WindINR, a latent…
- arXiv cs.AIresearchProposals and challenges for zero-knowledge verification of frontier AI training
arXiv:2606.05433v3 Announce Type: replace Abstract: Proposals for Frontier AI rules often use cumulative training compute as the main criterion for identifying high-impact models. Recent governance analyses call zero-kno…
- arXiv cs.AIresearchRethinking Synthetic Rationale Supervision for Disease Prediction
arXiv:2606.10279v2 Announce Type: replace Abstract: Supervised fine-tuning with synthetic rationales is widely assumed to improve clinical prediction by teaching models not only what to predict but why. We test this assu…
- arXiv cs.AIresearchTNODEV: Toolbox for Neural ODE Verification
arXiv:2606.16567v3 Announce Type: replace Abstract: Neural ordinary differential equations (neural ODE) gained attention in safety critical settings such as continuous-time controllers for cyber-physical systems and clas…
- arXiv cs.AIresearchBeyond Accuracy: Measuring Logical Compliance of Predictive Models
arXiv:2606.20208v2 Announce Type: replace Abstract: Machine learning models are predominantly evaluated through predictive performance metrics such as ranking quality, prediction error, or classification accuracy. While…
- arXiv cs.AIresearchDeepLook: Uncertainty-Guided Branching with Lookahead Confidence for Efficient Reasoning
arXiv:2607.22602v2 Announce Type: replace Abstract: Test-time scaling improves large language model reasoning, but spends compute uniformly along a reasoning trace, even in stretches that are already stable. Motivated by…
- arXiv cs.AIresearchLanguage Models Give Group-Linked Fields the Wrong Weight
arXiv:2608.22887v2 Announce Type: replace Abstract: Large language models are increasingly used to judge people, and their answers can depend on inputs correlated with a protected attribute such as race, even when that a…
- arXiv cs.AIresearchInterface-Induced Trajectory Censoring
arXiv:2609.03966v3 Announce Type: replace Abstract: Tool-use evaluations typically measure calls through a serving stack, which can report zero calls even when model outputs contain call-shaped payloads. We study interfa…
- arXiv cs.AIresearchWorld Models Under Asynchronous Sensor Observations
arXiv:2609.07299v2 Announce Type: replace Abstract: Learned world models typically assume that observations arrive synchronously, an abstraction inherited from simulators that return a complete state vector at each envir…
- arXiv cs.AIresearchAdaptive Entangled Neurons in the Brain and Natural Intelligence Simulations for Artificial General Intelligence
arXiv:2609.09226v2 Announce Type: replace Abstract: Understanding the brain's mechanisms is crucial in neuroscience, particularly for simulating natural intelligence and advancing artificial general intelligence (AGI). L…
- arXiv cs.AIresearchAI-driven Prices for Externalities and Sustainability in Production Markets
arXiv:2106.06060v5 Announce Type: replace-cross Abstract: Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the cost of over-approp…
- arXiv cs.AIresearchOptimized Conformal Selection: Powerful Selective Inference After Data-Dependent Score Construction
arXiv:2411.17983v2 Announce Type: replace-cross Abstract: We study data-driven score construction in conformal selection, which uses conformal p-values and multiple testing to select "interesting" instances with large un…
- arXiv cs.AIresearchAnnoCaseLaw: Legal Annotation Benchmark of Civil Negligence
arXiv:2503.00128v2 Announce Type: replace-cross Abstract: Language models offer a way to scale costly, labour-intensive expert annotation, but their ability to reproduce expert judgements remains uncertain. This is parti…
- arXiv cs.AIresearchQuantifying Symptom Causality in Clinical Decision Making: An Exploration Using CausaLM
arXiv:2503.19394v2 Announce Type: replace-cross Abstract: Current machine learning approaches to medical diagnosis often rely on correlational patterns between symptoms and diseases, risking misdiagnoses when symptoms ar…
- arXiv cs.AIresearchLearning to Interfere in Non-Orthogonal Multiple-Access Joint Source-Channel Coding
arXiv:2504.03690v2 Announce Type: replace-cross Abstract: We consider multiple transmitters aiming to communicate their source signals (e.g., images) over a multiple access channel (MAC). Conventional communication syste…
- arXiv cs.AIresearchQuantum-Inspired Optimization Process for Data Imputation
arXiv:2505.04841v3 Announce Type: replace-cross Abstract: Data imputation is a critical preprocessing step, particularly in clinical datasets where missingness can bias downstream inference. We propose a quantum-inspired…
- arXiv cs.AIresearchEffects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of LLMs in Ultimatum Games
arXiv:2505.24255v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for complex social interact…
- arXiv cs.AIresearchQuality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models
arXiv:2506.07121v3 Announce Type: replace-cross Abstract: Ensuring the safety and robustness of large language models (LLMs) is a fundamental challenge and a critical prerequisite for the responsible deployment of artifi…
- arXiv cs.AIresearchSpatiotemporal Reconstruction of Global Radiation from Sparse Sensor Sequences
arXiv:2506.12045v3 Announce Type: replace-cross Abstract: Much of the physical world is inaccessible to direct measurement and can be reached only through the sparse traces it leaves in other observable variables. Here w…
- arXiv cs.AIresearchAgriVLN: Vision-and-Language Navigation for Agricultural Robots
arXiv:2508.07406v2 Announce Type: replace-cross Abstract: Agricultural robots are serving as powerful members across a wide range of tasks, nevertheless, they are still heavily relying on manual operations or railway sys…
- arXiv cs.AIresearchUniPrompt-CL: Efficient Single-Inference Continual Learning for Medical Image Classification
arXiv:2508.10954v3 Announce Type: replace-cross Abstract: Medical AI systems must remain reliable as data distributions shift across hospitals, imaging devices, and patient populations, yet privacy constraints often prev…
- arXiv cs.AIresearchCan synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests
arXiv:2508.14936v4 Announce Type: replace-cross Abstract: Synthetic data hold substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns. However, many curren…
- arXiv cs.AIresearchHyperdimensional Probe: Decoding LLM Representations via Vector Symbolic Architectures
arXiv:2509.25045v4 Announce Type: replace-cross Abstract: Despite their capabilities, Large Language Models (LLMs) remain opaque with limited understanding of their internal representations. Current interpretability meth…