AI news archive.
10,661 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchVideo Generation Models: A Survey of Post-Training and Alignment
arXiv:2610.00812v1 Announce Type: cross Abstract: Video generation has rapidly progressed from short, low-quality clips to high-resolution, long-duration sequences with complex spatiotemporal dynamics. Despite strong gen…
- arXiv cs.AIresearchTraining-Aware Target Coverage for Synthetic Data Selection
arXiv:2610.00814v1 Announce Type: cross Abstract: Synthetic data are increasingly used to scale LLM training, yet more synthetic data do not necessarily produce better models. Useful synthetic data must add information r…
- arXiv cs.AIresearchTabJoinBench: A Benchmark for Joinable Table Discovery
arXiv:2610.00817v1 Announce Type: cross Abstract: Join discovery aims to identify tables from large data repositories that can augment a query table with complementary information, enabling downstream tasks such as data…
- arXiv cs.AIresearchOn-the-fly Weight Generation: A Hypernetwork Proof of Concept on ARC-1D
arXiv:2610.00820v1 Announce Type: cross Abstract: General-purpose models can adapt to many tasks from context, while specialised models can execute individual functions with less capacity. Yet obtaining such specialists…
- arXiv cs.AIresearchVerbalized and Internal Probabilities Are Coupled in Large Language Models
arXiv:2610.00827v1 Announce Type: cross Abstract: Large language models carry an internal notion of uncertainty in their sampling distribution, i.e., the probabilities they place on generating one answer rather than anot…
- arXiv cs.AIresearchContextual trajectory and incremental contextual displacement: Towards using LLMs to understand dynamic, utterance-specific meaning construction
arXiv:2610.00840v1 Announce Type: cross Abstract: Transformer-based large language models (LLMs) such as RoBERTa represent text using contextual word embeddings (CWEs), which alter the embeddings associated with each tok…
- arXiv cs.AIresearchGeometric Similarity in VLM Low-Level Vision Representations
arXiv:2610.00848v1 Announce Type: cross Abstract: Vision-language models (VLMs) have emerged as powerful candidates for universal vision backbones, with representative architectures including autoregressive (AR) models a…
- arXiv cs.AIresearchDon't Waste the Noise: Importance-Guided Perturbation Allocation under Joint Global and Local Constraints
arXiv:2610.00861v1 Announce Type: cross Abstract: Adversarial optimization under a shared $\ell_1$ budget requires deciding not only how much perturbation to use, but also where that limited budget should be spent. This…
- arXiv cs.AIresearchKinematic MeanFlow: One-Step Action Generation Policy for Robotic Foundation Models
arXiv:2610.00864v1 Announce Type: cross Abstract: In this paper, we study how to achieve one-step action generation in Robotic Foundation Models (RFMs), aiming to overcome the high inference latency of multi-step flow ma…
- arXiv cs.AIresearchRethinking Data Augmentation under Covariate Shift: Invariant-Guided Diffusion and Prototype Reweighting
arXiv:2610.00873v1 Announce Type: cross Abstract: In many industrial applications, 1) tabular data is scarce and imbalanced and thus requires synthetic expansion; 2) input distributions drift between training and deploym…
- arXiv cs.AIresearchMatch the Distribution, Not the Compute: Post-Training Multi-Token Prediction Heads
arXiv:2610.00888v1 Announce Type: cross Abstract: Multi-token prediction (MTP) improves the throughput of autoregressive generation by enabling the language model to draft multiple next tokens per forward pass, while a v…
- arXiv cs.AIresearchTOAST: Stochastic Robot Action Tokenization for Autoregressive Vision-Language-Action Models
arXiv:2610.00899v1 Announce Type: cross Abstract: Autoregressive Vision-Language-Action models often represent continuous robot actions as discrete token sequences, enabling action prediction with standard next-token obj…
- arXiv cs.AIresearchScrew Attention: Rigid-Body Algebra Inside a Transformer
arXiv:2610.00904v3 Announce Type: replace-cross Abstract: Learned manipulation policies rediscover from data the spatial relations that rigid-body mechanics supplies in closed form, which leaves them fragile to geometric…
- arXiv cs.AIresearchThe Geometry of Contextual Relations: Language Models Address Facts by Order of Mention
arXiv:2610.00910v1 Announce Type: cross Abstract: Human reasoning depends on how objects are related within propositions. \textit{How do relations organize the language representations of contextual contents?} We give an…
- arXiv cs.AIresearchReHoPER: Receding-Horizon Planning for Enhanced Reasoning
arXiv:2610.00940v1 Announce Type: cross Abstract: We propose ReHoPER, an inference-only, zero-shot method that improves large language models' reasoning by generating and answering intermediate questions along multiple p…
- arXiv cs.AIresearchA Matched-Budget Audit Framework for Recaptioned Image-Text Supervision Distributions
arXiv:2610.00952v1 Announce Type: cross Abstract: Recaptioned image-text corpora are now standard for text-to-image (T2I) training, with vision--language model (VLM) captioners replacing sparse alt-text by dense descript…
- arXiv cs.AIresearchTwo Clocks in Diffusion MLLMs: When Answers Stabilize Before Rationales Unfold
arXiv:2610.00953v1 Announce Type: cross Abstract: An answer candidate in a masked diffusion MLLM can stabilize while its rationale is still unfolding. We distinguish retrospective stabilization of the logged candidate fr…
- arXiv cs.AIresearchStructure-agnostic Causal Representation Learning
arXiv:2610.00968v1 Announce Type: cross Abstract: Causal representation learning aims to discover robust features by exploiting the causal structure underlying data generation. Existing methods require specifying the cau…
- arXiv cs.AIresearchA Citation-Grounded Benchmark for Trustworthy Earnings Call Transcript Analysis with Large Language Models
arXiv:2610.00969v1 Announce Type: cross Abstract: Large language models (LLMs) have been increasingly used for financial document analysis, including earnings call transcripts (ECTs). Beyond generating standalone claims,…
- arXiv cs.AIresearchRelationVGGT: Visual Geometry Transformers for 3D Spatial Relation Segmentation
arXiv:2610.00970v2 Announce Type: replace-cross Abstract: Recent advances in 3D reconstruction have progressed from per-scene optimization to feed-forward inference, and semantic scene understanding has followed suit --…
- arXiv cs.AIresearchGeneralist Representation, Specialist Detection: TS-Router for Time-Series Anomaly Detection
arXiv:2610.00978v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is difficult to generalize across datasets because heterogeneous temporal dynamics imply different notions of normality and favor dif…
- arXiv cs.AIresearchDivide-and-Remember: Recursive Action-Relevant Memory for Long-Horizon VLA Policies
arXiv:2610.00982v1 Announce Type: cross Abstract: Vision-language-action (VLA) models struggle on history-dependent manipulation tasks, where the current observation alone does not determine the action, and the policy ne…
- arXiv cs.AIresearchThe Devil Is in the Reconstruction Loss Scale: Rethinking Optimization in LLM Quantization
arXiv:2610.00983v1 Announce Type: cross Abstract: Post-training quantization (PTQ) methods typically use sequential quantization that partitions a pre-trained LLM into a series of units (e.g., transformer blocks), with o…
- arXiv cs.AIresearchDistilling Directional Verification
arXiv:2610.00997v1 Announce Type: cross Abstract: Knowledge distillation aims to transfer the factual knowledge of large language models to smaller models for efficient deployment. Yet a teacher may recall a relation in…
- arXiv cs.AIresearchOptimal Transport Reweighting for Robust Learning under Spurious Correlations and Label Noise
arXiv:2610.01028v1 Announce Type: cross Abstract: Machine learning models often suffer performance degradation under subpopulation shift, particularly when spurious correlations cause models to rely on shortcut features…
- arXiv cs.AIresearchPosterior sampling by source-space MCMC via prior-based few-step transport maps
arXiv:2610.01034v1 Announce Type: cross Abstract: Bayesian inference increasingly uses informative but implicit priors represented only by samples, such as historical ensembles, simulator outputs, and pretrained generati…
- arXiv cs.AIresearchCapturing In-Context Learning Dynamics with Task Operators
arXiv:2610.01054v1 Announce Type: cross Abstract: In-context learning (ICL) enables language models to perform new tasks from demonstrations without weight updates. However, every ICL inference requires processing the fu…
- arXiv cs.AIresearchMOMAT: Mixture of Multiple Atlases for Low-Power Jailbreak Defense of Quantized LLMs
arXiv:2610.01058v1 Announce Type: cross Abstract: Quantized large language models are increasingly deployed on edge devices for their low latency and energy efficiency. However, model quantization weakens alignment safeg…
- arXiv cs.AIresearchJoinGR: Learning to Traverse Join Graphs for Table Retrieval
arXiv:2610.01064v1 Announce Type: cross Abstract: Retrieving the right tables is a prerequisite for Text-to-SQL over realistic databases. Dense table retrievers rank schema elements independently, but this ignores a key…
- arXiv cs.AIresearchJev-IDS: System One Models for Network Intrusion Detection
arXiv:2610.01079v1 Announce Type: cross Abstract: Machine-learning Network Intrusion Detection Systems (IDS) depend on substantial labeled datasets and task-specific training, whereas Large Language Models (LLMs) detecti…
- arXiv cs.AIresearchOrbitTAMP: Grounding Language Models for Task and Motion Planning in Spacecraft Rendezvous
arXiv:2610.01093v1 Announce Type: cross Abstract: Spacecraft rendezvous and proximity operations (RPO) are currently planned through an expertise-intensive process in which engineers translate high-level operational inte…
- arXiv cs.AIresearchDoes Scaling Reinforcement Learning Really Require More Training?
arXiv:2610.01133v2 Announce Type: replace-cross Abstract: Scaling reasoning typically spends more compute on reinforcement learning (RL) or on inference. We show that a completed RL training history can yield policies st…
- arXiv cs.AIresearchParameter-Efficient Distributionally Robust Adaptation of Tabular Foundation Models under Subpopulation Shift
arXiv:2610.01143v1 Announce Type: cross Abstract: Despite strong mean accuracy, tabular foundation models (TFMs) can perform poorly on underrepresented groups under subpopulation shift, where group proportions change bet…
- arXiv cs.AIresearchWhen Is Deletion Ordering Tractable? From Update Dynamics to Permutation Structure
arXiv:2610.01149v1 Announce Type: cross Abstract: Given a fixed set of pending deletion requests, retraining from scratch after each request is prohibitive, so a prescribed request-wise policy processes them sequentially…
- arXiv cs.AIresearchLooping Beyond Twice: A Scalable Recipe for Looped Mixture-of-Experts
arXiv:2610.01153v1 Announce Type: cross Abstract: Looped Transformers introduce recurrent depth as a new scaling axis for LLMs: by repeatedly applying shared Transformer blocks, they increase effective depth without incr…
- arXiv cs.AIresearchCineMR: Tool-Integrated Vision-Language Reasoning for Quantitative Cardiac MRI Assessment
arXiv:2610.01166v2 Announce Type: replace-cross Abstract: Cardiovascular magnetic resonance (CMR), including cine imaging, is a reference standard for the noninvasive assessment of cardiac morphology and ventricular func…
- arXiv cs.AIresearchDetect, Explain, Interpret: An End-to-End Benchmark for Time Series Anomaly Detection, Explainability and Interpretability
arXiv:2610.01168v1 Announce Type: cross Abstract: Time Series Anomaly Detection has received increasing attention, driven by the growing availability of complex time series data. This surge has led to the development of…
- arXiv cs.AIresearchTemporally-Resolved Token Attribution Reveals the Generation Dynamics of Diffusion Language Models
arXiv:2610.01177v1 Announce Type: cross Abstract: This work presents Diffusion Layer Integrated Gradients (DLIG), a token attribution method for diffusion language models (DLMs) that extends Integrated Gradients (IG~\cit…
- arXiv cs.AIresearchReCast: Contract-Preserving Protection for Fixed-Interface Multimodal Reasoning
arXiv:2610.01184v1 Announce Type: cross Abstract: Remote multimodal models offer strong numerical reasoning capabilities over charts and speech, but sending private inputs risks exposing sensitive content. Text-only sani…
- 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.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.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…