AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchRegion-Guided Food-Package Evidence Extraction and Abstention-Aware Draft R3337 Screening with Selective VLM Review
arXiv:2610.28211v1 Announce Type: cross Abstract: Applying South Africa's draft R3337 warning criteria to food-package photographs requires nutrition, ingredient and product-form evidence. This study presents a region-gu…
- arXiv cs.AIresearchLocal Inference of LLMs on Long Contexts: A Data Systems Perspective
arXiv:2610.28223v1 Announce Type: cross Abstract: Large language models can solve complex problems across a variety of subjects, such as mathematics and coding. For such complex analytical tasks, models with a long conte…
- arXiv cs.AIresearchTPO: Tri-level Distributionally Robust Learning for OOD Direct Preference Optimization
arXiv:2610.28229v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) minimizes empirical risk over observed preference comparisons, implicitly assuming that the training preference distribution matches…
- arXiv cs.AIresearchPI-MLLM: Psychophysics-Inspired Multimodal Large Language Model for Oddly Satisfying Video Emotion Analysis
arXiv:2610.28264v1 Announce Type: cross Abstract: Oddly Satisfying Videos (OSVs) can evoke strong viewer responses through repetitive motion, visual tactility, and ASMR-like sounds despite containing few explicit semanti…
- arXiv cs.AIresearchVGL-stGen: Learning a shared multimodal model for lung histology and spatial transcriptomics
arXiv:2610.28266v1 Announce Type: cross Abstract: VGL-stGen is a multimodal large language model adapted from a pretrained medical vision-language model using paired lung H&E and spatial transcriptomics with single-cell…
- arXiv cs.AIresearchGALA: Geometry-Aware Language Model for Controllable Object Arrangement
arXiv:2610.28280v1 Announce Type: cross Abstract: Reasoning about fine-grained placement constraints, such as support and containment, is essential for realistic 3D scene creation. It remains a significant challenge for…
- arXiv cs.AIresearchABACUS: A Benchmark for Image Editing Models to Assess Object Category and Counting Under Scene Conservation
arXiv:2610.28316v1 Announce Type: cross Abstract: Instruction-based image editing models can now add, remove a specified number of objects or change their category while preserving the scene. Yet these models often fail…
- arXiv cs.AIresearchIdentifying Dependent Components from Multi-domain Linear Mixtures
arXiv:2610.28330v1 Announce Type: cross Abstract: We study a linear mixing model with dependent latent components, assuming multiple data domains. Most existing models assume that the components are independent or at lea…
- arXiv cs.AIresearchBeyond a Single Sentiment Score: Topical and Affective Dimensions of Emoji Meaning on Twitter
arXiv:2610.28337v1 Announce Type: cross Abstract: Emoji are widely treated as compact affective tokens whose meaning is summarised by a single sentiment score. We argue that this picture is incomplete. From a corpus of 1…
- arXiv cs.AIresearchGated Prototype Transfer for Zero-Support Medical Vision Language Model
arXiv:2610.28350v1 Announce Type: cross Abstract: Realistic few-shot adaptation of medical vision-language models (VLMs) can leave low-prevalence classes without any labeled support. The training-free SS- Text+ solver re…
- arXiv cs.AIresearchRayCo4D: Ray-Conditioned Continuous Motion Model for Monocular 4D Dynamic Reconstruction
arXiv:2610.28351v2 Announce Type: replace-cross Abstract: Reconstructing dynamic 3D scenes from monocular video requires inferring motion from noisy and intermittently visible observations. Long-range tracks provide valu…
- arXiv cs.AIresearchCountVideoBench: A Benchmark to Evaluate Prediction Biases on the Object Counting task by Video-Language Models
arXiv:2610.28356v3 Announce Type: replace-cross Abstract: Object counting in videos remains a poorly characterized capability of multimodal large language models. Counting questions are included in many existing VideoQA…
- arXiv cs.AIresearchContext-Aware Prompt Injection Detection via Small Language Models in RAG Pipelines: nokast-secureRAG
arXiv:2610.28364v1 Announce Type: cross Abstract: Local Retrieval-Augmented Generation (RAG) systems are vulnerable to indirect prompt injection and retrieval poisoning, where malicious instructions in retrieved content…
- arXiv cs.AIresearchDon't Skip the Baseline: A Controlled Comparison of Dynamic Expert Skipping in MoEs
arXiv:2610.28369v1 Announce Type: cross Abstract: A growing body of work proposes dynamic expert-skipping methods for Mixture-of-Experts (MoE) models that adjust the number of experts activated per token during inference…
- arXiv cs.AIresearchVisualEvolve: A Skill Self-Evolution Framework for Visual Reasoning
arXiv:2610.28386v1 Announce Type: cross Abstract: Visual tool use enables vision-language models (VLMs) to acquire task-relevant evidence, but its effectiveness can be limited by predefined visual operations and the tool…
- arXiv cs.AIresearchThe Instruction Tax on Factual Recall: Base Models Can Beat Their Instruction-Tuned Counterparts
arXiv:2610.28407v1 Announce Type: cross Abstract: We present our solution to the AKBC LM-KBC 2026 Shared Task, where we achieved a score of 0.6836 on the official leaderboard, more than double the baseline of 0.2964. Thi…
- arXiv cs.AIresearchBrain2Vec: A Self-Supervised 3D Foundation Model for Structural Brain MRI
arXiv:2610.28411v1 Announce Type: cross Abstract: Deep learning models have become essential tools in medical imaging, yet training them end-to-end for diverse tasks remains challenging due to limited labeled data and co…
- arXiv cs.AIresearchCode2Video-Compass: A Comprehensive Benchmark for General-Purpose Code-Based Video Generation across T2V, I2V, and V2V
arXiv:2610.28416v1 Announce Type: cross Abstract: Code-based video generation offers fine-grained control, targeted editing, and component reuse compared with direct video generation. This approach requires multimodal la…
- arXiv cs.AIresearchDISTRACT: Degradation-Indexed Study of Textual Reference Across Competing Targets
arXiv:2610.28419v1 Announce Type: cross Abstract: Vision-language trackers (VLTs) accept descriptions intended to assist tracking, but accepting text does not establish that its content changes tracking decisions, partic…
- arXiv cs.AIresearchWorldSR: Harnessing World Knowledge Search for Grounded Image Super-Resolution
arXiv:2610.28423v1 Announce Type: cross Abstract: Generative-prior-based super-resolution (SR) methods leverage implicit knowledge learned from large-scale models to enhance low-resolution inputs. However, such priors ar…
- arXiv cs.AIresearchRacer: Hunting GPU Kernel Bugs with Symbolic Equivalence Checking
arXiv:2610.28429v1 Announce Type: cross Abstract: GPU kernels are critical to the performance of today's AI services, yet the same operators are rewritten repeatedly: for each GPU generation, numeric format, serving regi…
- arXiv cs.AIresearchA Digital Twin to Improve Cyber-Social Impact
arXiv:2610.28430v1 Announce Type: cross Abstract: The increasing complexity of Industrial Control Systems (ICS) and their integration with IT infrastructures has significantly expanded the cyber threat landscape. Traditi…
- arXiv cs.AIresearchPlausible Future, Wrong Choice: Steering World-Action Models toward Intended Future
arXiv:2610.28431v1 Announce Type: cross Abstract: World-Action Models (WAMs) have emerged as a promising paradigm for embodied generalist policies by jointly modeling future world evolution and robot actions across diver…
- arXiv cs.AIresearchEvery Model Leaves a Trace: Multi-Resolution LLM Fingerprinting
arXiv:2610.28434v1 Announce Type: cross Abstract: Large language models leave model-specific traces in their generated text, but it remains unclear how finely these fingerprints can distinguish related models and which s…
- arXiv cs.AIresearchModel- and Layer-Level Closed-Loop Forecasting with SSM-Based Spiking Neural Networks
arXiv:2610.28495v1 Announce Type: cross Abstract: Deep State-Space Models (Deep SSMs) have shown promising performance and computational benefits in processing of time-series data with complex temporal dependencies. Spik…
- arXiv cs.AIresearchBitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
arXiv:2610.28500v1 Announce Type: cross Abstract: For efficient deployment of large language models (LLMs), methods of ultra-low-bit backbones reduce weight storage, memory traffic, and linear-layer execution cost, while…
- arXiv cs.AIresearchECG for laboratory values:A comprehensive physiological and technical analysis
arXiv:2610.28507v1 Announce Type: cross Abstract: Laboratory measurements are essential for clinical decision making but typically require invasive blood sampling. Recent research suggests that ECG recordings may contain…
- arXiv cs.AIresearchVLM-Guided Contact Retargeting and Generative Partner Modeling for Humanoid-Human Interaction
arXiv:2610.28523v1 Announce Type: cross Abstract: Humanoid-human interaction requires robots to operate under severe partial observability: during close physical contact, the human partner is occluded, truncated, or outs…
- arXiv cs.AIresearchBinary Discrete Diffusion: Candidate-Set Diffusion for Logic and Planning Tasks
arXiv:2610.28543v1 Announce Type: cross Abstract: Discrete diffusion models iteratively denoise a noisy sequence of categorical data such as text, enabling any-order generation with self-correction and in-filling capabil…
- arXiv cs.AIresearchLearning Computational Structure for Sample-Efficient Prediction
arXiv:2610.28555v1 Announce Type: cross Abstract: Statistical learning in high dimensions suffers from the curse of dimensionality. Fortunately, many functions of practical interest are compositionally sparse, meaning th…
- arXiv cs.AIresearchWhen Do LLMs Help with Feature Selection? A Systematic Empirical Study
arXiv:2610.28556v1 Announce Type: cross Abstract: Large language models (LLMs) can leverage semantic feature names alongside summary statistics for tabular feature selection, yet it remains unclear when such information…
- arXiv cs.AIresearchLarge Flow Language Models
arXiv:2610.28559v1 Announce Type: cross Abstract: Continuous flow language models offer a path to parallel generation with tools for control and acceleration unavailable to discrete diffusion, yet effective techniques fo…
- arXiv cs.AIresearchSpatially Informed and Direction Sensitive Representation Learning for Spatial Transcriptomics
arXiv:2610.28579v1 Announce Type: cross Abstract: Cellular states are shaped by both intrinsic gene expression programs and the spatial microenvironment in which cells reside. Spatial transcriptomics makes this context m…
- arXiv cs.AIresearchTurning TS2Vec into a Foundation Model for Time Series Classification
arXiv:2610.28602v1 Announce Type: cross Abstract: TS2Vec is one of the strongest self-supervised methods for time series classification, introduced in 2022. It is designed to be trained anew on every dataset: self-superv…
- arXiv cs.AIresearchBenchmarking Arabic Dialects for Math Problems
arXiv:2610.28607v1 Announce Type: cross Abstract: Mathematical reasoning remains underexplored for low-resource languages, including Dialectal Arabic. To bridge this gap, we introduce the DAR-MGSM (Dialectal Arabic Multi…
- arXiv cs.AIresearchMindView: Benchmarking Generative Multi-View Spatial Intelligence
arXiv:2610.28622v1 Announce Type: cross Abstract: Spatial intelligence has recently been assessed through generative tasks such as spatially grounded image editing, yet language-guided generation of spatially consistent…
- arXiv cs.AIresearchIndustrial ReMEmbR: Scaling Spatiotemporal Memory to Robot Fleets
arXiv:2610.28624v1 Announce Type: cross Abstract: Warehouse robot fleets continuously observe operational conditions, but preserving these observations as reusable semantic memory incurs substantial computation, communic…
- arXiv cs.AIresearchUniWALM: Unified World Action Language Model for Embodied Robot Control
arXiv:2610.28626v1 Announce Type: cross Abstract: Motivated by the human ability to integrate experience across language, perception, and action, we introduce UniWALM, a unified world-action-language model that learns vi…
- arXiv cs.AIresearchJoints, Camera, Action! Co-Generating 3D Motion and Video for Arbitrary Rigs
arXiv:2610.28632v1 Announce Type: cross Abstract: Video generation models can now depict remarkably realistic motion. Yet it is unclear how to use this motion beyond pixels: to animate a specific 3D asset and replay the…
- arXiv cs.AIresearchLLM-Guided Evolution of Symbolic Acceleration Inequality Families for MILP
arXiv:2508.11850v3 Announce Type: replace Abstract: Integer programming (IP) is central to many combinatorial optimization tasks but remains challenging due to its NP-hard nature. A practical way to improve IP solvers is…
- arXiv cs.AIresearchEMMA: Enhancing Robotic Control Robustness through a Generative Visual Model
arXiv:2509.22407v3 Announce Type: replace Abstract: The generalization of vision-language-action (VLA) models heavily relies on diverse training data. However, acquiring large-scale robot manipulation data across varied…
- arXiv cs.AIresearchMitigating Model Merging Conflicts via Knowledge-Aware Task Vector Purification
arXiv:2510.14697v2 Announce Type: replace Abstract: Model merging aims to integrate task-specific abilities from individually fine-tuned models into a single model without extra training. In recent model merging methods,…
- arXiv cs.AIresearchThe Reward Model Selection Crisis in Personalized Alignment
arXiv:2512.23067v3 Announce Type: replace Abstract: Personalized alignment from preference data has focused primarily on improving personal reward model (RM) accuracy, with the implicit assumption that better preference…
- arXiv cs.AIresearchTabular Foundation Models Can Learn Association Rules
arXiv:2602.14622v3 Announce Type: replace Abstract: Association Rule Mining (ARM) is a fundamental task for knowledge discovery in tabular data and is widely used in high-stakes decision-making. Classical ARM methods rel…
- arXiv cs.AIresearchMental Health AI Safety Claims Must Preserve Temporal Evidence
arXiv:2605.08827v3 Announce Type: replace Abstract: The safety of mental health AI is often judged at the wrong temporal scale. Current evaluations typically score isolated responses, endpoint outcomes, or aggregate dial…
- arXiv cs.AIresearchLearning Transferable Latent User Preferences for Human-Aligned Decision Making
arXiv:2605.12682v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as reasoning modules in many applications, yet they often struggle to produce human-aligned decisions. Human-aligned…
- arXiv cs.AIresearchBeyond a Single Direction: Chain-of-Thought Disrupts Simple Steering of Refusal
arXiv:2605.26772v2 Announce Type: replace Abstract: Large reasoning models (LRMs) generate chain-of-thought (CoT) traces before producing final outputs, introducing a dynamic internal state that may complicate control me…
- arXiv cs.AIresearchPReMISE: Policy Rubrics as Measurement Specifications for LLM Judges
arXiv:2605.30803v2 Announce Type: replace Abstract: LLM judges are increasingly used to evaluate open-ended responses, but their scores depend strongly on the rubrics that condition them. A vague rubric asking for a resp…
- arXiv cs.AIresearchThe Shape of Wisdom: How Language Models Converge on an Answer
arXiv:2606.01202v2 Announce Type: replace Abstract: When a language model answers a factual question, where does its internal state go? We asked four open models (Llama-3.1-8B, Qwen2.5-7B, Gemma-2-9B and Llama-3.2-1B) 2,…
- arXiv cs.AIresearchTeaching the Way, Not the Answer: Privileged Tutoring Distillation for Multimodal Policy Optimization
arXiv:2606.07000v2 Announce Type: replace Abstract: Recent post-training methods, particularly Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced the reasoning ability of Large Vision-Lang…