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UBP2: Uncertainty-Balanced Preference Planning for Efficient Preference-based Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2606.19328v2 Announce Type: replace Abstract: Preference-based RL provides an approach to learning reward models from pairwise comparisons of behaviors, bypassing the need for explicit reward de

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UECP: Uncertainty-Enhanced Collaborative Perception

DGX agent

arXiv:2606.23046v1 Announce Type: new Abstract: Collaborative perception serves as a pivotal solution to enhance the perception capability of individual agents in autonomous driving, where a core chal

agentsarxiv-cs-cv

23 Jun 2026

Ultra-Fusion: A Resilient Tightly-Coupled Multi-Sensor Fusion SLAM Framework under Sensor Degradation and Spatiotemporal Perturbation for Intelligent Transportation Systems

model-releasesarxiv-cs-ro

arXiv:2606.21223v1 Announce Type: new Abstract: Reliable localization is essential for intelligent transportation systems (ITS), including autonomous vehicles, quadruped last-mile carriers, and infras

Ultra-Peripheral Collisions as a Nuclear-Structure Interferometer with Interpretable Multitask Deep Learning

arXiv:2606.23353v1 Announce Type: cross Abstract: Precise knowledge of nuclear structure is essential across fundamental physics, yet probing these structures is notoriously difficult. To address this

Agents

UltraQuant: 4-bit KV Caching for Context-Heavy Agents

arXiv:2606.20474v2 Announce Type: replace Abstract: Context-heavy agents place unusual pressure on the key-value (KV) cache: long prefixes are reused across many short turns, while concurrency determi

agentsarxiv-cs-lg

Uncertainty-Aware Domain Adaptation for Vitiligo Segmentation in Clinical Photographs

arXiv:2512.11791v2 Announce Type: replace Abstract: Accurately quantifying vitiligo extent in routine clinical photographs is crucial for longitudinal monitoring of treatment response. We propose a tr

Understanding Latent Flow Models for Tabular Data Synthesis: Targets, Paths, and Sampling

arXiv:2606.20878v1 Announce Type: new Abstract: Synthetic tabular data enables microdata sharing in regulated domains, yet deploying continuous-time generative models requires balancing analytical uti

Understanding Parallel Samplers in Masked Diffusion via Random Walks on Graphs

model-releasesarxiv-cs-lg

arXiv:2606.22976v1 Announce Type: new Abstract: In this paper, we propose using random walks on graphs as a verifiable sandbox to study different parallel sampling strategies in masked diffusion model

UniFFBench: Evaluating Universal Machine Learning Force Fields Against Experimental Measurements

arXiv:2508.05762v3 Announce Type: replace-cross Abstract: Universal machine learning force fields (UMLFFs) promise to revolutionize materials science by enabling rapid atomistic simulations across the

applicationsarxiv-cs-lg

Unified Motion-Action Modeling for Heterogeneous Robot Learning

arXiv:2606.16917v3 Announce Type: replace Abstract: We present Unified Motion-Action (UMA) Model, an approach that uses 3D object motion trajectories as a shared interface to bridge visuomotor control

researcharxiv-cs-ro

UniFS: Unified Fast-to-Slow Hierarchical Architecture for Vision-Language-Action Models

arXiv:2606.22794v1 Announce Type: new Abstract: Mainstream Fast-Slow dual system vision-language-action models decouple a high-frequency action expert from a low-frequency vision-language model for ef

researcharxiv-cs-ro

UniRank: Unified Rank Allocation for Low-Rank LLM Compression

model-releasesarxiv-cs-lg

arXiv:2606.21847v1 Announce Type: new Abstract: Low-rank decomposition serves as a promising compression paradigm for large language models, however, rank allocation remains challenging: manual rules

UniSLAD: A Unified Framework for Structural and Logical Industrial Visual Anomaly Detection

arXiv:2606.20768v1 Announce Type: new Abstract: Visual anomaly detection is a fundamental task in industrial automation. While existing approaches have achieved notable progress in identifying structu

UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion

arXiv:2606.20971v1 Announce Type: new Abstract: We introduce UNITY, a Universal-to-Specialized adapter for efficient and scalable composite conditioning in diffusion based image generation. Unlike pri

safetyarxiv-cs-cv

UnityShots: Memory-Driven Multi-Shot Audio-Video Generation with Boundary-Aware Gating

arXiv:2606.21661v1 Announce Type: new Abstract: Generating a coherent multi-shot video requires structured cross-shot memory. Subject appearance, scene context, and speaker identity must persist acros

Universal Encoders for Modular Relational Deep Learning

arXiv:2606.21434v1 Announce Type: new Abstract: Relational Deep Learning (RDL) models multi-tabular databases as temporal heterogeneous graphs for end-to-end representation learning. While RDL is evol

Universal priors: solving empirical Bayes via Bayesian inference and pretraining

arXiv:2602.15136v2 Announce Type: replace-cross Abstract: We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achi

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation

arXiv:2606.23503v1 Announce Type: new Abstract: Vision Transformers (ViT) dominate computer vision. However, their reliance on rigid patch projectors hinders transfer to Earth Observation (EO), where

Agents

UniviewVLA: A Unified Multiview Vision-Language-Action Model with World Modeling

arXiv:2606.21501v1 Announce Type: new Abstract: Occluded tasks remain a bottleneck in robot manipulation. Existing solutions either deploy additional physical cameras requiring training-inference came

agentsarxiv-cs-ro

Unlimited OCR Works

arXiv:2606.23050v1 Announce Type: new Abstract: Recently, end-to-end OCR models, exemplified by DeepSeek OCR, have once again thrust OCR into the spotlight. A widely held view is that employing a larg

Unlocking In-Context Learning in Audio-Language Models from Decentralized Medical Audio

arXiv:2606.23243v1 Announce Type: new Abstract: Clinical audio diagnosis in low-resource settings requires models that identify conditions from minimal examples without large annotated corpora. We pro

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets

arXiv:2606.23204v1 Announce Type: new Abstract: Large-scale image-text datasets, such as LAION-5B, are foundational to modern AI systems, yet their vast scale and uncurated nature raise significant co

UNSEEN: Uncertainty-aware Navigation via Sparse Estimation in Unknown Environments

arXiv:2606.20755v1 Announce Type: new Abstract: Visual navigation in unknown environments remains a core challenge in mobile robotics, especially for resource-constrained platforms. Most existing appr

applicationsarxiv-cs-ro

Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability

arXiv:2606.21385v1 Announce Type: new Abstract: This paper explores unsupervised disentangled representation learning from a functional perspective. We define latent concepts as factors that influence

Unsupervised Domain Adaptation for Sim-to-Real Object Pose Estimation with Contrastive Alignment and Pseudo-Label Refinement

arXiv:2606.21287v1 Announce Type: new Abstract: Unsupervised domain adaptation (UDA) enables robust transfer of knowledge from simulated to real environments while exploiting a subset of unlabeled tar

safetyarxiv-cs-cv

Unsupervised Susceptibility Distortion Correction of EPI without Calibration Scans via Image Translation-Based Registration

arXiv:2606.21588v1 Announce Type: cross Abstract: Functional magnetic resonance imaging (fMRI) utilizes echo-planar imaging (EPI) to capture blood-oxygen-level-dependent (BOLD) signals with high tempo

Urban Power Grid Topology and Hierarchy Identification from Open Data

arXiv:2606.21352v1 Announce Type: new Abstract: Understanding the complex topology and hierarchy of urban power grid is crucial for energy prognosis, power flow management, and system resilience analy

Using predictive multiplicity to measure individual performance within the AI Act

arXiv:2602.11944v2 Announce Type: replace Abstract: When building AI systems for decision support, one often encounters the phenomenon of predictive multiplicity: a single best model does not exist; i

safetyarxiv-cs-lg

Variance-Tilted Diffusion Models for Diverse Sampling

arXiv:2606.22239v1 Announce Type: cross Abstract: Diffusion models are typically sampled independently, even when the downstream objective is to obtain a diverse set of candidates. We introduce a vari

Agents

VDAWorld: World Modelling via VLM-Directed Abstraction and Simulation

arXiv:2512.11061v2 Announce Type: replace Abstract: Generative video models, a leading approach to world modelling, face fundamental limitations. They often violate physical and logical rules, lack in

agentsarxiv-cs-cv

VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks

arXiv:2510.01022v3 Announce Type: replace Abstract: We introduce vector diffusion wavelets (VDWs), a novel family of wavelets inspired by the vector diffusion maps algorithm that was introduced to ana

applicationsarxiv-cs-lg

Hardware

Vec-QMDP: Vectorized POMDP Planning on CPUs for Real-Time Autonomous Driving

arXiv:2602.08334v2 Announce Type: replace Abstract: Planning under uncertainty for real-world robotics tasks, such as autonomous driving, requires reasoning in enormous high-dimensional belief spaces,

hardwarearxiv-cs-ro

VegSim: A Geospatial World Model for Scenario-Conditioned Vegetation Simulation

arXiv:2606.21961v1 Announce Type: new Abstract: Vegetation monitoring under climate stress requires answering not only how it will evolve given the expected weather, but how it would respond to altern

applicationsarxiv-cs-lg

Venice-H1: Failure-Aware Query Re-Ranking with Multi-Scale Grid Signatures for Referring Image Segmentation

arXiv:2606.22546v1 Announce Type: new Abstract: Modern Referring Image Segmentation (RIS) systems generate multiple candidate masks per expression but rely on a simple heuristic--typically the argmax

Vera: A Layered Diffusion Model for Content-Preserving Video Editing

arXiv:2606.23610v1 Announce Type: new Abstract: Video diffusion models have enabled remarkable progress in video generation and editing. However, content preservation remains a core challenge: existin

VeriBound: PAC-Bayesian Generalization Bounds for Process Reward Models Trained with Formal Verification Tools

arXiv:2606.20740v1 Announce Type: cross Abstract: Process Reward Models (PRMs) provide step-level verification for Large Language Model (LLM) reasoning, yet their training data acquisition remains a b

VeriEvol: Scaling Multimodal Mathematical Reasoning via Verifiable Evol-Instruct

arXiv:2606.23543v1 Announce Type: cross Abstract: Scaling reinforcement learning for visual mathematical reasoning requires more than generating harder questions: as data volume grows, the reward labe

Local Ai

Vesta: A Generalist Embodied Reasoning Model

arXiv:2606.20905v1 Announce Type: new Abstract: Robots operating in open-world environments must seamlessly integrate localization, spatial reasoning, navigation, and long-horizon planning. While spec

local-aiarxiv-cs-ro

Video2Code: Generating Interactive Webpages from UI Videos via Action-Aware Revisit

arXiv:2606.20711v1 Announce Type: new Abstract: UI videos provide a natural input for generating interactive webpages, as they capture both webpage appearance and action-triggered state transitions. H

VideoAgent: All-in-One Framework for Video Understanding and Editing

arXiv:2606.23327v1 Announce Type: new Abstract: Video editing has become essential in digital media creation, yet existing automated systems are restricted to short segment processing and domain-speci

VideoLatent: Video-Language Learning via Latent Self-Forcing

arXiv:2606.22870v1 Announce Type: new Abstract: Recent advancements in chain-of-thought (CoT) reasoning have shown promise in enhancing video understanding and reasoning capabilities of multimodal lar

safetyarxiv-cs-cv

Vision-language models for chest radiography do not always need the image

arXiv:2606.17710v2 Announce Type: replace Abstract: Medical vision-language models report strong chest radiograph accuracy, and this is increasingly read as evidence that they use the image. That infe

Visual Geometry Transformer in the Wild: Distractor-Free 3D Reconstruction

arXiv:2606.22787v1 Announce Type: new Abstract: Current end-to-end multi-view 3D reconstruction methods achieve impressive results, but rely on a restrictive static assumption: the scenes is entire di

applicationsarxiv-cs-cv

VLA-FAIL: Efficient Task Failure Detection for Finetuned Vision-Language-Action Models

arXiv:2606.21386v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) achieve state-of-the-art performance on many robotic manipulation tasks, yet they can still behave unpredictably

applicationsarxiv-cs-cv

VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies

arXiv:2602.21445v2 Announce Type: replace Abstract: Action chunking has recently emerged as a standard practice in flow-based Vision-Language-Action (VLA) models. However, the effect and choice of the

applicationsarxiv-cs-ro

VolHuMe: a High-Resolution Large Scale Dataset of Volumetric Human Meshes

arXiv:2606.23062v1 Announce Type: cross Abstract: We introduce VolHuMe, a dataset of high-quality 4D human scans captured with a state-of-the-art volumetric studio using 64 RGB and 32 depth cameras. V

VQActFlow: Vector-Quantized Action Mode Steering for Multi-Task Robot Manipulation

arXiv:2606.21600v1 Announce Type: new Abstract: Multi-task robot manipulation policies are challenging to learn from demonstration because traditionally a single network must select among qualitativel

safetyarxiv-cs-ro

VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-Training

arXiv:2508.03058v2 Announce Type: replace Abstract: Reinforcement Learning (RL) in real-world environments often suffers from ambiguous or incomplete reward supervision, which undermines policy stabil

safetyarxiv-cs-lg