AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchCroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets
arXiv:2610.07132v1 Announce Type: cross Abstract: Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful reading of accompanying…
- arXiv cs.AIresearchCLM-as-a-Judge: Evaluating an Open Contrastive Decision Model on Public Judge Benchmarks
arXiv:2610.07177v1 Announce Type: cross Abstract: An open contrastive decision model is near chance as a judge on the hard public benchmarks: Contrastive-LM/CLM-v0.1-8B scores between 0.351 (best- of-four, chance 0.250)…
- arXiv cs.AIresearchResponsible Institutional Analytics: Interpreting Bias with AI Support
arXiv:2610.07205v1 Announce Type: cross Abstract: Institutional Analytics (IA) dashboards inform decision-making in higher education, yet data limitations, constraints in analytical techniques, and missing contextual inf…
- arXiv cs.AIresearchDistributionally Robust Mixture-of-Experts Training
arXiv:2610.07207v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) transformers scale capacity by activating only a few experts per token, but this sparsity creates a hidden reliability problem: when routing is i…
- arXiv cs.AIresearchRoboCap: A New Platform for Egocentric Robot Learning
arXiv:2610.07217v2 Announce Type: replace-cross Abstract: Despite its promise for scaling robot learning, egocentric manipulation data is still scarce today. Collection at scale requires vertically integrating ergonomic…
- arXiv cs.AIresearchTIDE 2.0: an open, model-agnostic engine for keyed de-identification of clinical notes
arXiv:2610.07224v1 Announce Type: cross Abstract: Clinical notes capture most of what is documented about a patient's care, but they cannot be used for research until protected health information (PHI) is removed. De-ide…
- arXiv cs.AIresearchMinimal Witness Reinforcement Learning
arXiv:2610.07226v3 Announce Type: replace-cross Abstract: ``What are the irreducible conditions that are sufficient to produce an outcome?'' is one of the most common questions that recur across computation and science.…
- arXiv cs.AIresearchSAFESHIELD: A Decision-Organization Framework for Deployment-Time Safety of Small Language Models
arXiv:2610.07276v1 Announce Type: cross Abstract: Deployment-time safety of language models is commonly implemented through runtime guardrails such as input moderation, routing, retrieval verification, and output filteri…
- arXiv cs.AIresearchPolar: LLM-Powered Synthesis of Real-World Cyber Evidence for Prioritization and Mitigation
arXiv:2610.07298v1 Announce Type: cross Abstract: Cyber threat analysis increasingly depends on evidence distributed across vendor advisories, vulnerability databases, and threat intelligence sources. Turning these fragm…
- arXiv cs.AIresearchFrom Sandbox to Enforcement: Confidence-Qualified Threat Intelligence for Critical Infrastructure
arXiv:2610.07310v1 Announce Type: cross Abstract: Security operations centres and national incident-response teams defending critical infrastructure collect abundant threat data yet struggle to turn it into actionable in…
- arXiv cs.AIresearchScale-Invariant Training for Time Series Foundation Models
arXiv:2610.07324v2 Announce Type: replace-cross Abstract: Time series foundation models (TSFMs) are trained on large collections of time series datasets that span various morphologies and domains. This setting exposes mo…
- arXiv cs.AIresearchMemory-Efficient Expert Routing for Distributed MoE Training
arXiv:2610.07333v1 Announce Type: cross Abstract: As Mixture-of-Experts (MoE) models scale toward hundreds of experts and higher top-$k$ routing, memory efficiency in distributed training becomes a critical bottleneck. P…
- arXiv cs.AIresearchLogbook: Extremely Long-form Audio Event Understanding
arXiv:2610.07338v1 Announce Type: cross Abstract: Audio benchmarks are built around short, pre-segmented clips, limiting model design to brief inputs or fixed vocabularies. To close this gap, we introduce Logbook, a benc…
- arXiv cs.AIresearchA doctrine-grounded visual question answering dataset for Tactical Combat Casualty Care
arXiv:2610.07339v1 Announce Type: cross Abstract: Tactical Combat Casualty Care (TC3) requires responders to connect visual observations of injuries and interventions with established clinical guidance. Developing vision…
- arXiv cs.AIresearchCausalBind: Causal Modeling and Learning for Protein-Molecule Virtual Screening
arXiv:2610.07340v1 Announce Type: cross Abstract: Protein-molecule virtual screening is increasingly cast as a problem of representation learning in a shared embedding space. Existing methods rely on dense holistic align…
- arXiv cs.AIresearchStepped MoE: Segment-Level Routing with Configurable Inference Complexity
arXiv:2610.07348v1 Announce Type: cross Abstract: Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging…
- arXiv cs.AIresearchA Validated Dataset and Benchmark for Coherent Multi-Diagram SysML Models
arXiv:2610.07356v1 Announce Type: cross Abstract: Systems engineers use several diagrams to describe the structure and behavior of systems. Engineers create these diagrams together to make sure that they use the same ele…
- arXiv cs.AIresearchWildMatch: Weakly Supervised Image Matcher Adaptation for Wildlife Re-Identification
arXiv:2610.07384v1 Announce Type: cross Abstract: Individual animal re-identification from camera-trap imagery is an instance retrieval problem central to non-invasive wildlife monitoring: a query image must retrieve the…
- arXiv cs.AIresearchDeepAJM: Deep Association Joint Model for Irregularly Sampled data
arXiv:2610.07388v2 Announce Type: replace-cross Abstract: Joint Models simultaneously model longitudinal and survival outcomes, leveraging patterns in patients' longitudinal trajectory to improve the prediction of surviv…
- arXiv cs.AIresearchInference and learning in sparse autoencoders as natural gradient flow
arXiv:2610.07389v1 Announce Type: cross Abstract: Sparse autoencoders are widely used to uncover interpretable features in neural networks, yet reliable recovery remains difficult when features overlap or activate infreq…
- arXiv cs.AIresearchActive Feature Acquisition for Cost-Efficient Temporal Prediction with Reduced Participant Burden
arXiv:2610.07452v1 Announce Type: cross Abstract: Accurate forecasting of pathological outcomes is a central problem in psychology. To do so, psychologists often collect intensive longitudinal data. However, in such stud…
- arXiv cs.AIresearchAlignQuant: Tile-Aligned Mixed-Precision Quantization for Efficient LLM Generation
arXiv:2610.07457v1 Announce Type: cross Abstract: Fine-grained mixed-precision quantization promises efficient large language model inference, but local precision choices can conflict with regular GPU storage and computa…
- arXiv cs.AIresearchElasticFit: Fit-Aware 3D Object Insertion via VLM Reasoning and Generative Adaptation
arXiv:2610.07460v2 Announce Type: replace-cross Abstract: Inserting objects into existing 3D scenes requires more than selecting a plausible location: the inserted object must also fit local geometry while preserving sem…
- arXiv cs.AIresearchStructure, Not Belief: Correlated Thompson Sampling from LLM-Derived Covariance in Combinatorial Semi-Bandits
arXiv:2610.07470v1 Announce Type: cross Abstract: Combinatorial Thompson sampling (CTS) draws independent posterior samples for every arm, so its exploration dynamics ignore any relation among arms. We study a minimal ch…
- arXiv cs.AIresearchCan Power Draw Constrain Covert Compute? Limits of Analogue Verification for AI Governance
arXiv:2610.07476v1 Announce Type: cross Abstract: Frontier AI treaties or agreements on limiting computation require external verification; an external auditor must be able to confirm how much computation actually ran an…
- arXiv cs.AIresearchHarmful SFT Leaves a Continuous Trace in LLM Checkpoint Updates
arXiv:2610.07518v1 Announce Type: cross Abstract: Safety auditing of post-trained large language models typically relies on model behavior, requiring model execution and depending on the coverage of available evaluations…
- arXiv cs.AIresearchSafeguarding LLMs via Model-Agnostic Latent Safety Signals from Dark Knowledge
arXiv:2610.07532v1 Announce Type: cross Abstract: LLMs have advanced rapidly, raising growing concerns about their safety. Recent work has proposed approaches to detect and defend against attacks including defenses at de…
- arXiv cs.AIresearchWhich and When to Admit: Gradient Admission for Data-Centric Small Language Model Finetuning
arXiv:2610.07553v1 Announce Type: cross Abstract: LoRA fine-tuning adapts small language models (SLMs) to heterogeneous instruction data within a low-rank update subspace, making it vulnerable to three structural problem…
- arXiv cs.AIresearchSeeing the Invisible: Physics-Guided Visual Prompting for Temperature- and Radiation-Aware VLA Navigation
arXiv:2610.07558v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have become a major paradigm for Vision-and-Language Navigation (VLN). However, in safety-critical facilities, invisible risks such as…
- arXiv cs.AIresearchLearning a Mixture of GFlowNets
arXiv:2610.07562v1 Announce Type: cross Abstract: Learning an ensemble of GFlowNets to sample from a discrete target distribution has become a common approach for achieving better state space exploration and convergence…
- arXiv cs.AIresearchComplementary Feature Domains: Information Preservation Does Not Imply Predictive-Contribution Preservation
arXiv:2610.07565v1 Announce Type: cross Abstract: Complementary Feature Domains (CFD) theory characterizes predictive value as a context-indexed contribution system induced jointly by representations and their realizatio…
- arXiv cs.AIresearchOpenSplatGraph: From Dense Semantic Maps to Structured Scene Graphs for Open-Vocabulary Robot Perception
arXiv:2610.07569v1 Announce Type: cross Abstract: Dense 3D mapping with semantic understanding is essential for robotic perception in complex environments. Recent 3D Gaussian Splatting-based mapping approaches enable hig…
- arXiv cs.AIresearchMechanistic Interpretability of Atmospheric Rivers in GraphCast
arXiv:2610.07583v1 Announce Type: cross Abstract: While AI weather models now rival operational forecasts, how they represent the atmosphere internally remains an open question: feature attribution reveals which input pa…
- arXiv cs.AIresearchRecurrent Looped Transformer
arXiv:2610.07591v2 Announce Type: replace-cross Abstract: State tracking requires an update at every input, but the depth a Transformer applies to each token is fixed regardless of sequence length. We introduce the Recur…
- arXiv cs.AIresearchModeling Latent Disturbances for Robust Decision-Making in World Models
arXiv:2610.07599v1 Announce Type: cross Abstract: In this paper, we study robust decision-making in the latent space of world models (WMs). Robust optimization is a mathematical framework where, given explicitly specifie…
- arXiv cs.AIresearchEmoception: Selective Affective Layer Fine-Tuning of Video Vision Transformers for Player Arousal Change Recognition From Gameplay Footage
arXiv:2610.07603v1 Announce Type: cross Abstract: This article proposes Selective Affective Layer Fine-Tuning (SALFT), an efficient adaptation framework for Video Vision Transformers in player arousal recognition from ga…
- arXiv cs.AIresearchLinear Fitness Subspace in Protein Language Models Enables Sample-Efficient Directed Evolution
arXiv:2610.07607v1 Announce Type: cross Abstract: Model-guided directed evolution seeks to identify high-fitness protein variants under limited oracle budgets. Protein language models (PLMs) provide rich representations…
- arXiv cs.AIresearchMonte Carlo Estimation for KV Cache Eviction
arXiv:2610.07643v2 Announce Type: replace-cross Abstract: Most KV-cache eviction methods ask, in effect, which memory appeared important while reading the prompt? We instead ask which memory will matter while answering?…
- arXiv cs.AIresearchSMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining
arXiv:2610.07652v1 Announce Type: cross Abstract: The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations for these interaction…
- arXiv cs.AIresearchDoes On-Policy Distillation for Safety Pose Backdoor Risks?
arXiv:2610.07654v1 Announce Type: cross Abstract: On-policy distillation (OPD) has attracted growing attention as an effective way to transfer capabilities from teacher models to student models. Recent studies further ex…
- arXiv cs.AIresearchSENSE: State-aware Emotion Navigation Storytelling Engine
arXiv:2610.07666v1 Announce Type: cross Abstract: This paper presents SENSE, a state-aware framework for generating playable branching visual novels with multi-track emotional navigation. Integrating a state-based narrat…
- arXiv cs.AIresearchCACHEFORGE: LLM-Guided End-to-End Generative Cache Replacement Policy for Performance and Hardware Efficiency
arXiv:2610.07668v1 Announce Type: cross Abstract: Modern cache replacement designs saturate because they operate within fixed representational structures, hand-crafted and heuristic based feature-engineered predictors, o…
- arXiv cs.AIresearchExact-Solution Volume and Length Generalization in Transformers
arXiv:2610.07676v1 Announce Type: cross Abstract: Research on transformer expressivity shows whether a transformer is capable of solving a given task, but gives little indication of whether the solution, if learned, is g…
- arXiv cs.AIresearchEigenDEXplore: Structured Exploration for Dexterous Manipulation with Human Priors
arXiv:2610.07681v2 Announce Type: replace-cross Abstract: Dexterous manipulation poses a challenging high-dimensional optimization problem, as useful behaviors require coordinated motion across many hand joints. In reinf…
- arXiv cs.AIresearchDisentangling Dual Image References in Frequency Aware Diffusion Models for Personalized Generation
arXiv:2610.07684v1 Announce Type: cross Abstract: Personalized image generation aims to synthesize text-driven images conditioned on reference images, while mainly casting the generation as image customization for foregr…
- arXiv cs.AIresearchWhat Frame-Level Labels Can and Cannot Do for Small-UAV Point Detection in Thermal Video
arXiv:2610.07705v1 Announce Type: cross Abstract: The growing use of unmanned aerial vehicles (UAVs) has increased the importance of image-based UAV detection. Learning-based detectors are trained on imagery and annotati…
- arXiv cs.AIresearchWASD: Wasserstein-based Knowledge Distillation for Large Language Models
arXiv:2610.07706v1 Announce Type: cross Abstract: Autoregressive large language models (LLMs) have rapidly advanced in capability, but their increasing scale comes with substantial computational and memory costs at infer…
- arXiv cs.AIresearchSanSi: A Looped Typed Decision Model for System 1.5 Thinking
arXiv:2610.07730v2 Announce Type: replace-cross Abstract: Typed decision models answer a declared question without generating text: a decision head returns a probability for each of the declared options in a single forwa…
- arXiv cs.AIresearchLearning to Retrieve via Reinforcement Learning in Embedding Space
arXiv:2610.07731v1 Announce Type: cross Abstract: Dense retrieval models are typically trained with contrastive objectives that learn effective representations but do not directly optimize retrieval metrics or downstream…
- arXiv cs.AIresearchCleave: Scaling Tensor Program Optimization via Decoupled Algebraic Search and Operator Scheduling
arXiv:2610.07742v1 Announce Type: cross Abstract: Optimized kernels such as FlashAttention and FlashDecoding are crucial for accelerating today's large models. Most of them are handwritten by experts because existing ML…