AI news archive.
19,854 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchCounterfactual Generation via Flow Matching: Coupling-Sensitive End-to-End Rates
arXiv:2610.01193v1 Announce Type: cross Abstract: Counterfactual generation seeks to sample outcomes under a hypothetical intervention or decision using observational data collected under the factual assignment mechanism…
- arXiv cs.AIagentsHave an LLM Write Your Anomaly Detector: Autonomous Discovery of Compact, Interpretable Detectors for Time Series
arXiv:2610.01223v1 Announce Type: cross Abstract: Time-series anomaly detection trades off predictive accuracy, computational efficiency, and interpretability. We use a large language model not as the detector but as the…
- arXiv cs.AIresearchJudgement in the Age of Jev: From Evaluation Scarcity to Evaluation Abundance
arXiv:2610.01231v1 Announce Type: cross Abstract: Generative artificial intelligence has reduced the cost of producing plausible symbolic artefacts, leading recent organisation scholarship to identify evaluation and disc…
- arXiv cs.AIresearchWhen the Judge Acts: Auditing VLM-Guided Image Selection on Culturally Situated Prompts
arXiv:2610.01243v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly act as judges that pick the best of several generated images, so their choices decide what users see. Such judges are usually v…
- arXiv cs.AIresearchScience Utopia? Closed-Loop LLM Simulation of Academic Research Ecosystems
arXiv:2610.01257v1 Announce Type: cross Abstract: Scientific progress emerges from a longitudinal ecosystem in which researchers, institutions, funding agencies, collaboration networks, and the scientific literature co-e…
- arXiv cs.AIresearchPROMO: Preference-conditioned Multi-Objective Reinforcement Learning for Quadrupedal Robots
arXiv:2610.01260v1 Announce Type: cross Abstract: Quadrupedal locomotion requires balancing conflicting objectives such as command tracking, stability, and energy efficiency, yet conventional reinforcement learning (RL)…
- arXiv cs.AIresearchPickMoment: Continuous-Time Single-Image-to-Video via Learning Deblurring and Blur-to-Video
arXiv:2610.01279v1 Announce Type: cross Abstract: Motion blur arises from the temporal integration of a continuous sharp signal over a finite exposure window, yet existing learning-based methods sidestep this physical mo…
- arXiv cs.AIresearchModel validation in machine learning: A scenario-based guide from hold-out splits to nested group cross-validation in biomedical and applied research
arXiv:2610.01284v1 Announce Type: cross Abstract: Model validation estimates the performance of a complete learning procedure on new data. However, an invalid split can produce an optimistic and stable result. This tutor…
- arXiv cs.AIresearchFederated Learning for LLMs over Mobile Networks: Issues and Solutions in the RAN Transport
arXiv:2610.01304v1 Announce Type: cross Abstract: Federated LLM fine-tuning enables large models to be adapted using private and geographically distributed data at the network edge, creating recurring and deadline-sensit…
- arXiv cs.AIresearchFeature Selective Model Collapse in Diffusion Models: Total Replacement versus Fixed-Budget Training
arXiv:2610.01318v1 Announce Type: cross Abstract: Model collapse arises when generative models are trained on synthetic data produced by earlier models. The phenomenon has attracted considerable attention because of its…
- arXiv cs.AIagentsPACE: Provenance-Aware Capability Enforcement for Tool-Using LLM Agents
arXiv:2610.01349v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents turn generated text into real side effects, so poisoned tool metadata, retrieved pages, memory, and reusable skills can steer…
- arXiv cs.AIresearchDiscrete Wasserstein Flows for One-Step Generative Modeling
arXiv:2610.01355v1 Announce Type: cross Abstract: We introduce a new framework for one-step generative modelling on finite state spaces. To extend drifting beyond continuous domains, we use discrete Wasserstein geometry…
- arXiv cs.AIresearchFold'EM: Direct atomic structure inference from Cryo-EM particles
arXiv:2610.01358v2 Announce Type: replace-cross Abstract: Single-particle cryo-electron microscopy (cryo-EM) has become a widely adopted technique for biomolecular structure determination. The conventional cryo-EM comput…
- arXiv cs.AIagentsLLM-Driven Multi-Agent Control for Skill-Based Smart Manufacturing
arXiv:2610.01364v1 Announce Type: cross Abstract: Factories are shifting toward smaller lot sizes with high product customization, requiring frequent re-programming of flexible and reconfigurable automation systems. LLM-…
- arXiv cs.AIresearchSupervising Sound Localization by In-the-wild Egomotion
arXiv:2610.01388v1 Announce Type: cross Abstract: We present a method for learning binaural sound localization using egomotion as a supervisory signal. Over the course of a video, the cameras direction to a sound source…
- arXiv cs.AIresearchLLM-Assisted Discovery of Typed Semantic Links for Ontology Network Construction
arXiv:2610.01393v1 Announce Type: cross Abstract: Constructing typed, justified semantic links between ontologies is essential for enabling interoperability across heterogeneous and interdisciplinary knowledge domains. H…
- arXiv cs.AIresearchOptimal Transport Meets Reinforcement Learning: A Survey
arXiv:2610.01413v1 Announce Type: cross Abstract: Reinforcement learning (RL) algorithms frequently compare probability distributions, such as state visitation distributions induced by policies and experts, action distri…
- arXiv cs.AIresearchGeneralization Is Stability, Not Accuracy: Multi-Axis Evaluation of LLMs
arXiv:2610.01428v1 Announce Type: cross Abstract: Generalization in large language models (LLMs) is the ability to produce consistent and semantically stable outputs when the same input is expressed in different ways. Ex…
- arXiv cs.AIresearchMWOP: Modality-aware Width-wise Operation Pruning for Efficient MLLMs
arXiv:2610.01434v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) incur substantial inference costs when processing long visual-textual sequences. While existing operation compression methods exp…
- arXiv cs.AIresearchWhen Does a Second Model Help? Cross-Model Review in LLM Verification
arXiv:2610.01471v2 Announce Type: replace-cross Abstract: Large language models now generate code, documentation, and analyses, and are increasingly used to review such output. We ask when a second review by a different…
- arXiv cs.AIresearchMulti-Party Backchannel Prediction: a Diagnosis, a Benchmark, and a Ceiling
arXiv:2610.01488v1 Announce Type: cross Abstract: Backchannel prediction has been studied almost entirely in dyadic conversation. We introduce a multi-party benchmark based on the AMI corpus, comprising 682 masked-listen…
- arXiv cs.AIresearchNo Model Required: Text Entropy Rate Filtering Mitigates Iterative Fine-Tuning Collapse
arXiv:2610.01493v1 Announce Type: cross Abstract: Iterative fine-tuning on synthetic data causes \emph{model collapse}: output diversity narrows as rare patterns are progressively lost, a signature most visible as phrase…
- arXiv cs.AIresearchFedMIX-P: Mixing Local and Global Preconditioners for Federated Vision and Language Model Training
arXiv:2610.01515v1 Announce Type: cross Abstract: Adaptive preconditioners accelerate model training, but heterogeneous client geometries can bias federated updates even when gradients are evaluated at the same model. Ro…
- arXiv cs.AIresearchAuto-Formalizing Neuro-Symbolic Predictors
arXiv:2610.01519v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) predictors incorporate prior knowledge into the prediction process of neural networks, ensuring that outputs satisfy specified constraints, making t…
- arXiv cs.AIresearchExact Distinguishability in Non-Markovian Decision Processes
arXiv:2610.01527v1 Announce Type: cross Abstract: Non-Markovian environments are often modeled as Regular Decision Processes (RDPs), where dynamics depend on the interaction history through a finite automaton. Existing o…
- arXiv cs.AIresearchFalse Floors: LLM Safety Routing Evaluations Break Under Distribution Shift
arXiv:2610.01535v1 Announce Type: cross Abstract: Safety routers send each request to one of several models and are judged against the best single model. A major routing benchmark picks that comparator on the evaluation…
- arXiv cs.AIresearchReinforcement Learning to Accelerate Primal-Dual Hybrid Gradient for Linear Programming
arXiv:2610.01546v1 Announce Type: cross Abstract: Primal-dual hybrid gradient (PDHG) methods solve large-scale linear programs (LPs) using GPU-friendly matrix-vector products and projections, but their practical performa…
- arXiv cs.AIresearchCompletion Aware Guidance for World Action Models
arXiv:2610.01559v2 Announce Type: replace-cross Abstract: World Action Models (WAMs) predict visual futures and robot actions, yet they remain susceptible to task-incomplete imagination, where plausible, action-consisten…
- arXiv cs.AIagentsChaining Skills to Hijack LLM Agents
arXiv:2610.01564v1 Announce Type: cross Abstract: LLM agents use skills to improve performance on specialized tasks. To complete a user request, an agent may invoke several skills in sequence, allowing information produc…
- arXiv cs.AIagentsManaging Context and Communication in Distributed Agentic UAV Swarms
arXiv:2610.01569v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) swarms increasingly rely on language-model agents to provide adaptive mission-level reasoning in uncertain environments. Fully distributed c…
- arXiv cs.AIresearchBeyond Pointwise Error: A Multi-Metric Evaluation of Spatial Climate Downscaling
arXiv:2610.01579v1 Announce Type: cross Abstract: Climate downscaling aims to reconstruct fine scale spatial fields from coarse resolution inputs. Evaluating the quality of these reconstructions is challenging: low point…
- arXiv cs.AIresearchBefore It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs
arXiv:2610.01595v1 Announce Type: cross Abstract: Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet temporal reasoning remain…
- arXiv cs.AIresearchPermutation-Robust Decision Modeling with Candidate-Independent Block-Causal Attention
arXiv:2610.01601v1 Announce Type: cross Abstract: Decision models often score a variable-sized set of candidate actions encoded in a single sequence. This setting is increasingly relevant for System 1 components inside g…
- arXiv cs.AIresearchHob-VL: A Benchmark for Visually Grounded Boolean Reasoning
arXiv:2610.01605v1 Announce Type: cross Abstract: Reliable visual reasoning requires composing multiple visual observations and returning consistent answers to logically equivalent questions. We introduce Hob-VL, a bench…
- arXiv cs.AIresearchCan LLMs Reliably Annotate Bioassay Metadata to Improve Data Readiness?
arXiv:2610.01616v1 Announce Type: cross Abstract: The emergence of foundation models for molecular property prediction requires a high degree of AI data readiness, including reliable metadata annotation. However, both pu…
- arXiv cs.AIresearchExposing the Cost of Deep Learning Audio Development
arXiv:2610.01619v1 Announce Type: cross Abstract: The environmental impact of deep learning has attracted increasing attention over the past decade. Existing studies mainly focus on the energy and carbon emissions of mod…
- arXiv cs.AIresearchWhat Makes Something Hard(er)? Explaining Question Difficulty in Natural Language
arXiv:2610.01627v1 Announce Type: cross Abstract: Difficulty is one of the most fundamental properties of a question: it determines whether the question can meaningfully discriminate between models of differing ability.…
- arXiv cs.AIresearchNot All Error Yields to Scale: Where Scaling Stops in Vision-Language Inference
arXiv:2610.01640v1 Announce Type: cross Abstract: Vision-language models (VLMs) face a fixed-budget trade-off between processing more visual information for fine-grained perception and using a larger language backbone fo…
- arXiv cs.AIresearchMCIR: A Feature Dependence-Aware Explainability Method with Reliability Guarantees
arXiv:2610.01641v1 Announce Type: cross Abstract: Modern machine-learning models often contain strongly dependent or redundant features, making feature attribution difficult because shared predictive information can be d…
- arXiv cs.AIresearchIterative Policy Refinement through Semantic Rollout Analysis
arXiv:2610.01652v1 Announce Type: cross Abstract: Structured policies improve efficiency, robustness, and interpretability in imitation learning by introducing task-specific inductive bias, but existing structure generat…
- arXiv cs.AIresearchArchitectural Sampling: Test-Time Scaling via Computational Diversity in Frozen Vision-Language Models
arXiv:2610.01687v1 Announce Type: cross Abstract: Test-time scaling often seeks better answers by sampling multiple responses from a frozen model, yet conventional temperature sampling generates every candidate along the…
- arXiv cs.AIresearchArchitecture Without an Architect? Global Governance of Artificial Intelligence in a Divided World
arXiv:2610.01716v1 Announce Type: cross Abstract: Artificial intelligence presents an unusually difficult problem for global governance. The technology develops rapidly, crosses borders easily, and is shaped by actors wh…
- arXiv cs.AIresearchRemoving spurious minima for planar features by skip connections
arXiv:2610.01728v2 Announce Type: replace-cross Abstract: Understanding loss landscapes is central to explaining neural-network training, yet their structure remains only partially understood even in simple models. We st…
- arXiv cs.AIresearchCog-VADU: A Training-Free Cognitive Reasoning Framework for Video Anomaly Detection and Understanding
arXiv:2610.01754v1 Announce Type: cross Abstract: Video Anomaly Detection (VAD) aims to temporally localize abnormal events in videos. Most existing approaches rely on dataset-specific training and curated annotations, l…
- arXiv cs.AIagentsSoK: Decentralized Agent Economic Infrastructure
arXiv:2610.01756v1 Announce Type: cross Abstract: Decentralized agent economies increasingly build a single task from protocols that were designed and secured separately. This creates a simple problem: a workflow can loo…
- arXiv cs.AIresearchCODesign: Consistency from Data to Trajectory in All-Atom Protein Binder Co-Design
arXiv:2610.01773v1 Announce Type: cross Abstract: The central challenge in de novo protein design is generating plausible, mutually compatible structures and sequences, such that each designed sequence folds into its int…
- arXiv cs.AIresearchVETO: Video Efficient Token Optimization for Vision Language Models
arXiv:2610.01785v1 Announce Type: cross Abstract: Processing long videos with Vision-Language Models (VLMs) is bottlenecked by the quadratic cost of visual tokens, making long-form inference prohibitively expensive. Whil…
- arXiv cs.AIresearchiADD: Improving Alignment and Diversity in Diffusion Policy Optimization
arXiv:2610.01789v1 Announce Type: cross Abstract: Reinforcement learning based post training of diffusion models, such as Denoising Diffusion Policy Optimization (DDPO), optimizes a reverse diffusion process under a rewa…
- arXiv cs.AIagentsToken Communication-Assisted Collaborative Embodied Artificial Intelligence: Concepts, Framework, and Opportunities
arXiv:2610.01826v1 Announce Type: cross Abstract: Collaborative embodied artificial intelligence (CEAI) enables multiple physical agents to perceive, reason, and act cooperatively in dynamic environments. Effective commu…
- arXiv cs.AIresearchDetecting Inconsistencies in Model Specifications with LLM-as-Verifier Reasoning
arXiv:2610.01847v1 Announce Type: cross Abstract: Model specifications define how large language models (LLMs) should behave, guiding alignment training, inference-time behavior, and evaluation. Yet these specifications…