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VDFP: Video Deflickering with Flicker-banding Priors

arXiv:2605.21079v1 Announce Type: new Abstract: Capturing digital screens with smartphones frequently induces severe banding due to hardware synchronization mismatches. Existing video restoration meth

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Human DGX agent

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Velocityformer: Broken-Symmetry-Matched Equivariant Graph Transformers for Cosmological Velocity Reconstruction

DGX agent

arXiv:2605.21483v1 Announce Type: cross Abstract: Precise measurement of the kinematic Sunyaev-Zel'dovich (kSZ) effect - a probe of the large-scale distribution of baryonic matter, a key observable fo

safetyarxiv-cs-lg

21 May 2026

Verifiable Error Bounds for Physics-Informed Neural Network Solutions of Lyapunov and Hamilton-Jacobi-Bellman Equations

arXiv:2603.19545v2 Announce Type: replace-cross Abstract: Many core problems in nonlinear systems analysis and control can be recast as solving partial differential equations (PDEs) such as Lyapunov a

safetyarxiv-cs-lg

Verifiable Provenance and Watermarking for Generative AI: An Evidentiary Framework for International Operational Law and Domestic Courts

arXiv:2605.21002v1 Announce Type: cross Abstract: Generative artificial intelligence now synthesizes photorealistic imagery, audio, and video at a cost that defeats traditional forensic intuition. The

Tutorials

Verification of Unknown Dynamical Systems via Autoencoder Latent Space

arXiv:2512.13593v4 Announce Type: replace Abstract: Formal verification provides a powerful framework for proving that dynamical systems satisfy their specifications. However, these techniques face sc

tutorialsarxiv-cs-lg

VersusQ: Pairwise Margin Reasoning for Generalizable Video Quality Assessment

arXiv:2605.21130v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have shown promise for video quality assessment, but most methods still predict an absolute score for each video. Such po

VIHD: Visual Intervention-based Hallucination Detection for Medical Visual Question Answering

arXiv:2605.20772v1 Announce Type: new Abstract: While medical Multimodal Large Language Models (MLLMs) have shown promise in assisting diagnosis, they still frequently generate hallucinated responses

researcharxiv-cs-cv

Vision Transformers and Convolutional Neural Networks for Land Use Scene Classification

arXiv:2605.21268v1 Announce Type: new Abstract: Land Use Scene Classification (LUSC) from remote sensing imagery plays a critical role in environmental monitoring, urban planning, and sustainable reso

VISTA: Technical Report for the Ego4D Short-Term Object Interaction Anticipation at EgoVis 2026

arXiv:2605.20901v1 Announce Type: new Abstract: We propose VISTA, a V-JEPA Integrated StillFast Temporal Anticipator for the Ego4D Short-Term Object Interaction Anticipation (STA) Challenge at EgoVis

VISTAQA: Benchmarking Joint Visual Question Answering and Pixel-Level Evidence

arXiv:2605.20676v1 Announce Type: new Abstract: Establishing a clear link between model predictions and the visual evidence that supports them is critical for transparency and reliability in multimoda

VLA-REPLICA: A Low-Cost, Reproducible Benchmark for Real-World Evaluation of Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2605.20774v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, but their real-world evaluation remains limited

VLANeXt: Recipes for Building Strong VLA Models

arXiv:2602.18532v2 Announce Type: replace Abstract: Following the rise of large foundation models, Vision-Language-Action models (VLAs) emerged, leveraging strong visual and language understanding fro

safetyarxiv-cs-cv

VSCD: Video-based Scene Change Detection in Unaligned Scenes

arXiv:2605.20821v1 Announce Type: new Abstract: Detecting what has changed in an environment is essential for long-term autonomy, yet most change detection settings assume fixed viewpoints, mild misal

WaveGraphNet: Physics-Consistent Guided-Wave Damage Localization through Coupled Inverse-Forward Graph Learning

arXiv:2605.20311v1 Announce Type: new Abstract: Guided-wave structural health monitoring enables damage localization in composite plates using sparse networks of bonded piezoelectric transducers. Howe

WCXB: A Multi-Type Web Content Extraction Benchmark

arXiv:2605.21097v1 Announce Type: new Abstract: Web content extraction - isolating a page's main content from surrounding boilerplate - is a prerequisite for search indexing, retrieval-augmented gener

Weasel: Out-of-Domain Generalization for Web Agents via Importance-Diversity Data Selection

arXiv:2605.20291v1 Announce Type: new Abstract: Large language models (LLMs) have enabled web agents that follow natural language goals through multi-step browser interactions. However, agents fine-tu

Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics

arXiv:2605.20441v1 Announce Type: new Abstract: Transformers trained on modular arithmetic exhibit sharp transitions between memorization, generalization, and collapse. We show that weight decay acts

Applications

WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems

arXiv:2603.14392v2 Announce Type: replace Abstract: Trajectory world models play a crucial role in robotic dynamics learning, planning, and control. While recent works have explored trajectory world m

applicationsarxiv-cs-lg

What Do Biomedical NER and Entity Linking Benchmarks Measure? A Corpus-Centric Diagnostic Framework

arXiv:2605.20537v1 Announce Type: new Abstract: Biomedical named entity recognition (NER) and entity linking (EL) strongly depend on annotated corpora, but the utility of these resources for benchmark

Agents

What if Agents Could Imagine? Reinforcing Open-Vocabulary HOI Comprehension through Generation

arXiv:2602.11499v2 Announce Type: replace Abstract: Multimodal Large Language Models have shown promising capabilities in bridging visual and textual reasoning, yet their reasoning capabilities in Ope

agentsarxiv-cs-cv

What Semantics Survive the Connector? Diagnosing VLM-to-DiT Alignment in Video Editing

arXiv:2605.20795v1 Announce Type: new Abstract: Flow matching based video generative models have been increasingly relying on prepended Vision-Language Models (VLMs) to handle complex, instruction-bas

safetyarxiv-cs-cv

What Twelve LLM Agent Benchmark Papers Disclose About Themselves: A Pilot Audit and an Open Scoring Schema

arXiv:2605.21404v1 Announce Type: new Abstract: We read twelve well-known LLM agent benchmark papers and recorded, dimension by dimension, what each paper actually says about how its evaluation was ru

When AI Gets it Wrong: Reliability and Risk in AI-Assisted Medication Decision Systems

arXiv:2604.01449v3 Announce Type: replace-cross Abstract: Artificial intelligence (AI) systems are increasingly integrated into healthcare and pharmacy workflows, supporting tasks such as medication r

safetyarxiv-cs-lg

When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control

arXiv:2601.18973v4 Announce Type: replace Abstract: Quantum hardware suffers from intrinsic device heterogeneity and environmental drift, forcing practitioners to choose between suboptimal non-adaptiv

When Irregularity Helps: A Subclass Analysis of Inductive Bias in Neural Morphology

arXiv:2605.20558v1 Announce Type: new Abstract: Neural morphological generation systems often achieve high aggregate accuracy on benchmark datasets, yet such performance can conceal systematic errors

When Reasoning Supervision Hurts: TTCW-Based Long-Form Literary Review Generation

arXiv:2605.20364v1 Announce Type: new Abstract: Automatic evaluation of long-form literary writing remains challenging, as generic LLM-as-Judge approaches may not fully capture creativity-related dime

researcharxiv-cs-cl

When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency

arXiv:2603.09024v2 Announce Type: replace Abstract: Sudden concept drift makes previously trained predictors unreliable, yet deciding when to retrain and what post-drift data size is sufficient is rar

Why Aggregate Accuracy is Inadequate for Evaluating Fairness in Law Enforcement Facial Recognition Systems

arXiv:2603.28675v2 Announce Type: replace Abstract: Facial recognition systems are increasingly deployed in law enforcement and security contexts, where algorithmic decisions can carry significant soc

safetyarxiv-cs-cv

Why Ask One When You Can Ask k? Learning-to-Defer to the Top-k Experts

arXiv:2504.12988v5 Announce Type: replace Abstract: Existing Learning-to-Defer (L2D) frameworks are limited to single-expert deferral, forcing each query to rely on only one expert and preventing the

safetyarxiv-cs-lg

Agents

Why Latent Actions Fail, and How to Prevent It

arXiv:2605.20223v1 Announce Type: new Abstract: Latent action models (LAMs) aim to learn action-like representations from unlabeled videos by compressing frame-to-frame changes. The frames of in-the-w

agentsarxiv-cs-cv

WikiVQABench: A Knowledge-Grounded Visual Question Answering Benchmark from Wikipedia and Wikidata

arXiv:2605.21479v1 Announce Type: new Abstract: Visual Question Answering (VQA) benchmarks have largely emphasized perception-based tasks that can be solved from visual content alone. In contrast, man

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents

arXiv:2605.20306v1 Announce Type: new Abstract: We introduce WildRoadBench, a wild aerial road-damage grounding benchmark that couples direct visual grounding by vision-language models with autonomous

Winfree Oscillatory Neural Network

arXiv:2605.20922v1 Announce Type: cross Abstract: Oscillations and synchronization are widely believed to play a fundamental role in representation and computation. However, existing machine learning

Tutorials

WiXus: A Wheeled-Legged Robot with Wire-Driven Environmental Utilizing to Integrate Mobility and Manipulation

arXiv:2605.20932v1 Announce Type: new Abstract: Wheeled-legged robots, which have wheels at their feet and achieve high mobility by coordinating wheel drive and leg drive, have been developed. These r

tutorialsarxiv-cs-ro

You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks

arXiv:2506.09521v2 Announce Type: replace-cross Abstract: Speaker anonymization systems hide the identity of speakers while preserving other information such as linguistic content and emotions. To eva

researcharxiv-cs-cl

Local Ai

You Don't Need Attention: Gated Convolutional Modeling for Watch-Based Fall Detection

arXiv:2605.20275v1 Announce Type: new Abstract: Existing deep learning approaches for wearable fall detection systems rely on self-attention mechanisms that impose quadratic computational overhead, di

local-aiarxiv-cs-cv

You Only Need Minimal RLVR Training: Extrapolating LLMs via Rank-1 Trajectories

arXiv:2605.21468v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a dominant paradigm for improving reasoning in large language models (LLMs), yet the

ZEBRA: Zero-shot Budgeted Resource Allocation for LLM Orchestration

arXiv:2605.20485v1 Announce Type: new Abstract: As autonomous agents increasingly execute end-to-end tasks under fixed monetary budgets, the pressing open question shifts from whether the budget is re

3D aperture-engineered diffractive neural networks for super-resolution electromagnetic wave computing

arXiv:2603.00995v2 Announce Type: replace-cross Abstract: The rapid progress in 6G communication and high-bandwidth radar has driven an unprecedented surge in the spatial density of signal sources, re

researcharxiv-cs-ai

Local Ai

3D Modeling and Automated Measurement of Concrete Cracks via Segment Anything Refinement and Visual Inertial LiDAR Fusion

arXiv:2501.09203v2 Announce Type: replace Abstract: Visual-Spatial Systems has become increasingly essential in concrete crack inspection. However, existing methods often lacks adaptability to diverse

local-aiarxiv-cs-cv

3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion

arXiv:2404.07106v2 Announce Type: replace Abstract: Point cloud completion aims to generate a complete and high-fidelity point cloud from an initially incomplete and low-quality input. A prevalent str

researcharxiv-cs-cv

A Bitter Lesson for Data Filtering

model-releasesarxiv-cs-ai

arXiv:2605.19407v1 Announce Type: cross Abstract: We investigate data filtering for large model pretraining via new scaling studies that target the high compute, data-scarce regime. In spite of an app

A Case for Agentic Tuning: From Documentation to Action in PostgreSQL

model-releasesarxiv-cs-ai

arXiv:2605.19988v1 Announce Type: cross Abstract: Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only w

Agents

A Closed-loop, State-centric, Multi-agent Framework for Passenger Load Estimation from Heterogeneous Data Streams

arXiv:2605.19834v1 Announce Type: cross Abstract: To support operations and passenger-facing services, transit agencies need reliable passenger load trajectories. Currently, load estimates are typical

agentsarxiv-cs-ai

A Cloud-Based Tool for Meteorite Recovery Using Drones and Machine Learning

arXiv:2605.19179v1 Announce Type: cross Abstract: We present a cloud-based tool that uses drones and machine learning to help recover instrumentally observed meteorite falls. We showcase a collection

A Data-Driven Approach to Idiomaticity Based on Experts' Criteria in Theoretical Linguistics

arXiv:2605.19575v1 Announce Type: new Abstract: The article observes data analysis of 286 multi-word expressions (MWEs) based on 16 lexical, grammatical and other criteria described in theoretical boo

researcharxiv-cs-cl

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

A Family of Divergence Measures for Evaluating the Reconstruction Quality of Explainable Ensemble Trees

arXiv:2605.19618v1 Announce Type: new Abstract: Validating interpretable surrogate models for ensemble learners requires measuring agreement between the ensemble's internal representation and its surr