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Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation

arXiv:2604.24763v1 Announce Type: new Abstract: Unified multimodal models typically rely on pretrained vision encoders and use separate visual representations for understanding and generation, creatin

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Turtle shell clustering: A mixture approach to discriminative clustering with applications to flow cytometry and other data

DGX agent

arXiv:2604.23083v1 Announce Type: cross Abstract: Generative approaches to clustering provide information on geometric properties of clusters, whereas discriminative approaches provide boundaries betw

researcharxiv-cs-lg

28 Apr 2026

U-ViLAR: Uncertainty-Aware Visual Localization for Autonomous Driving via Differentiable Association and Registration

arXiv:2507.04503v2 Announce Type: replace Abstract: Accurate localization using visual information is a critical yet challenging task, especially in urban environments where nearby buildings and const

local-aiarxiv-cs-cv

UGAF-ITS: A Standards Harmonization Framework and Validation Tool for Multi-Framework AI Governance in Distributed Intelligent Transportation Systems

arXiv:2604.22789v1 Announce Type: cross Abstract: Organizations deploying AI-enabled Intelligent Transportation Systems face fragmented governance: ISO/IEC 42001 demands a certifiable management syste

Ulterior Motives: Detecting Misaligned Reasoning in Continuous Thought Models

arXiv:2604.23460v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning has emerged as a key technique for eliciting complex reasoning in Large Language Models (LLMs). Although interpretable,

Uncertainty Propagation in LLM-Based Systems

arXiv:2604.23505v1 Announce Type: cross Abstract: Uncertainty in large language model (LLM)-based systems is often studied at the level of a single model output, yet deployed LLM applications are comp

Uncertainty Quantification for LLM Function-Calling

arXiv:2604.22985v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed to autonomously solve real-world tasks. A key ingredient for this is the LLM Function-Calling par

agentsarxiv-cs-cl

Unconstrained Multi-view Human Pose Estimation with Algebraic Priors

arXiv:2604.24312v1 Announce Type: cross Abstract: Recovering 3D human pose from multi-view imagery typically relies on precise camera calibration, which is often unavailable in real-world scenarios, t

applicationsarxiv-cs-ai

Uncovering Latent Patterns in Social Media Usage and Mental Health: A Clustering-Based Approach Using Unsupervised Machine Learning

arXiv:2604.24611v1 Announce Type: new Abstract: The widespread adoption of social media has heightened interest in its psychological effects, particularly on mental health indicators such as anxiety,

Understanding Representation Gaps Across Scales in Tropical Tree Species Classification from Drone Imagery

arXiv:2604.23019v1 Announce Type: new Abstract: Accurate classification of tropical tree species from unoccupied aerial vehicle (UAV) imagery remains challenging due to high species diversity and stro

safetyarxiv-cs-cv

Understanding the Limits of Automated Evaluation for Code Review Bots in Practice

arXiv:2604.24525v1 Announce Type: cross Abstract: Automated code review (ACR) bots are increasingly used in industrial software development to assist developers during pull request (PR) review. As ado

UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems

arXiv:2604.23362v1 Announce Type: cross Abstract: Adversarial attacks play a pivotal role in testing and improving the reliability of deep learning (DL) systems. Existing literature has demonstrated t

safetyarxiv-cs-lg

Unified Multi-Foundation-Model Slide Representation for Pan-Cancer Recognition and Text-Guided Tumor Localization

arXiv:2604.22846v1 Announce Type: new Abstract: The expanding ecosystem of pathology foundation models has produced powerful but fragmented tile-level representations, limiting their use in clinical t

local-aiarxiv-cs-cv

Universal Approximation of Operators with Transformers and Neural Integral Operators

arXiv:2409.00841v3 Announce Type: replace Abstract: We study the universal approximation properties of transformers and neural integral operators for operators in Banach spaces. In particular, we show

Tutorials

Universal approximation property of Banach space-valued random feature models including random neural networks

arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel

tutorialsarxiv-cs-lg

Unleashing the Agility of Wheeled-Legged Robots for High-Dynamic Reflexive Obstacle Evasion

arXiv:2604.23761v1 Announce Type: new Abstract: Wheeled-legged robots combine the energy efficiency of wheeled locomotion with the terrain adaptability of legged systems, making them promising platfor

applicationsarxiv-cs-ro

Unrealized Expectations: Comparing AI Methods vs Classical Algorithms for Maximum Independent Set

arXiv:2502.03669v3 Announce Type: replace-cross Abstract: AI methods, such as generative models and reinforcement learning, have recently been applied to combinatorial optimization (CO) problems, espe

local-aiarxiv-cs-ai

UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks

arXiv:2604.23141v1 Announce Type: cross Abstract: Emerging AR-LLM-based Social Engineering attack (e.g., SEAR) is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attac

Unstable Rankings in Bayesian Deep Learning Evaluation

arXiv:2604.23102v1 Announce Type: new Abstract: Standard evaluations of Bayesian deep learning methods assume that metric estimates are reliable, but we show this assumption fails under data scarcity.

Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training

arXiv:2604.24350v1 Announce Type: cross Abstract: Fast Adversarial Training (FAT) has attracted significant attention due to its efficiency in enhancing neural network robustness against adversarial a

UpstreamQA: A Modular Framework for Explicit Reasoning on Video Question Answering Tasks

arXiv:2604.23145v1 Announce Type: cross Abstract: Video Question Answering (VideoQA) demands models that jointly reason over spatial, temporal, and linguistic cues. However, the task's inherent comple

Urban Flood Observations (UFO): A hand-labeled training and validation dataset of post-flood inundation

arXiv:2604.23066v1 Announce Type: new Abstract: Urban flooding affects lives and infrastructure worldwide. Mapping inundation in complex urban environments from satellite imagery remains challenging d

Usable Agent Discovery for Decentralized AI Systems

arXiv:2604.23080v1 Announce Type: cross Abstract: Large-scale agentic systems run on distributed infrastructures where many software agents share physical hosts and are discovered via peer-to-peer mec

agentsarxiv-cs-ai

Using Language Models as Closed-Loop High-Level Planners for Robotics Applications: A Brief Overview and Benchmarks

arXiv:2511.07410v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Vision Language Models (VLMs) have become popular tools for embodied high-level planning. However, their depl

Utility-Aware Data Pricing: Token-Level Quality and Empirical Training Gain for LLMs

arXiv:2604.22893v1 Announce Type: cross Abstract: Traditional data valuation methods based on ``row-count imes quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that

V-GRPO: Online Reinforcement Learning for Denoising Generative Models Is Easier than You Think

arXiv:2604.23380v1 Announce Type: cross Abstract: Aligning denoising generative models with human preferences or verifiable rewards remains a key challenge. While policy-gradient online reinforcement

safetyarxiv-cs-cv

V-SEAM: Visual Semantic Editing and Attention Modulating for Causal Interpretability of Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2509.14837v2 Announce Type: replace Abstract: Recent advances in causal interpretability have extended from language models to vision-language models (VLMs), seeking to reveal their internal mec

Value Alignment Tax: Measuring Value Trade-offs in LLM Alignment

arXiv:2602.12134v2 Announce Type: replace Abstract: Existing work on value alignment typically characterizes value relations statically, ignoring how alignment interventions, such as prompting, fine-t

VAMP-Net: An Interpretable Multi-Path Network of Genomic Permutation-Invariant Set Attention and Quality-Aware 1D-CNN for MTB Drug Resistance

arXiv:2512.21786v2 Announce Type: replace Abstract: Genomic prediction of drug resistance in Mycobacterium tuberculosis is often hindered by complex epistatic interactions and variable sequencing qual

VAPO: End-to-end Slide-Enhanced Speech Recognition with Omni-modal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2510.08618v2 Announce Type: replace-cross Abstract: Omni-modal large language models (OLLMs) offer a promising end-to-end solution for slide-enhanced speech recognition due to their inherent mul

Variational Grey-Box Dynamics Matching

arXiv:2602.17477v3 Announce Type: replace Abstract: Deep generative models such as flow matching and diffusion models have shown great potential in learning complex distributions and dynamical systems

applicationsarxiv-cs-lg

VDLF-Net: Variational Feature Fusion for Adaptive and Few-Shot Visual Learning

arXiv:2604.23641v1 Announce Type: new Abstract: This paper introduces VDLF-Net, which attaches a compact VAE to a multi-scale CNN backbone. Latent vectors and softmax-gate support the backbone feature

Verifying Quantized GNNs With Readout Is Decidable But Highly Intractable

arXiv:2510.08045v2 Announce Type: replace-cross Abstract: We introduce a logical language for reasoning about quantized aggregate-combine graph neural networks with global readout (ACR-GNNs). We provi

VeriLLMed: Interactive Visual Debugging of Medical Large Language Models with Knowledge Graphs

arXiv:2604.23356v1 Announce Type: new Abstract: Large language models (LLMs) show promise in medical diagnosis, but real-world deployment remains challenging due to high-stakes clinical decisions and

applicationsarxiv-cs-cl

Vibe Medicine: Redefining Biomedical Research Through Human-AI Co-Work

arXiv:2604.23674v1 Announce Type: new Abstract: With the emergence of large language models (LLMs) and AI agent frameworks, the human-AI co-work paradigm known as Vibe Coding is changing how people co

agentsarxiv-cs-ai

Viewport-Unaware Blind Omnidirectional Image Quality Assessment: A Unified and Generalized Approach

arXiv:2604.23953v1 Announce Type: cross Abstract: Blind omnidirectional image quality assessment (BOIQA) presents a great challenge to the visual quality assessment community, due to different storage

Vision-Based Lane Following and Traffic Sign Recognition for Resource-Constrained Autonomous Vehicles

arXiv:2604.22872v1 Announce Type: new Abstract: Autonomous vehicles (AVs) rely on real-time perception systems to understand road environments and ensure safe navigation. However, implementing reliabl

local-aiarxiv-cs-cv

Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines

arXiv:2604.23001v1 Announce Type: cross Abstract: Despite remarkable progress in Vision--Language--Action (VLA) models, a central bottleneck remains underexamined: the data infrastructure that underli

Vision-Language-Action Safety: Threats, Challenges, Evaluations, and Mechanisms

arXiv:2604.23775v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are emerging as a unified substrate for embodied intelligence. This shift raises a new class of safety challenges, s

safetyarxiv-cs-ro

Visual Funnel: Resolving Contextual Blindness in Multimodal Large Language Models

arXiv:2512.10362v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) demonstrate impressive reasoning capabilities, but often fail to perceive fine-grained visual details

VitaminP: cross-modal learning enables whole-cell segmentation from routine histology

arXiv:2604.23799v1 Announce Type: new Abstract: Accurate whole-cell and nuclear segmentation is essential for precision pathology and spatial omics, yet routine hematoxylin and eosin (H&E) staining pr

Voxify3D: Pixel Art Meets Volumetric Rendering

arXiv:2512.07834v2 Announce Type: replace Abstract: Voxel art is a distinctive stylization widely used in games and digital media, yet automated generation from 3D meshes remains challenging due to co

safetyarxiv-cs-cv

VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation

arXiv:2604.22942v1 Announce Type: cross Abstract: Diffusion models produce high-quality synthetic data but suffer from slow inference. We propose 3D Variable-Step Denoising Diffusion Probabilistic Mod

Weakly Supervised Multicenter Nancy Index Scoring in Ulcerative Colitis Using Foundation Models

arXiv:2604.23706v1 Announce Type: new Abstract: Histologic assessment of ulcerative colitis (UC) activity is an important endpoint in clinical trials and routine care, but manual grading with indices

WeatherSeg: Weather-Robust Image Segmentation using Teacher-Student Dual Learning and Classifier-Updating Attention

arXiv:2604.22824v1 Announce Type: cross Abstract: WeatherSeg, an advanced semi-supervised segmentation framework, addresses autonomous driving's environmental perception challenges in adverse weather

agentsarxiv-cs-ai

WebSerial Vision Training for Microcontrollers: A Browser-Based Companion to On-Device CNN Training

model-releasesarxiv-cs-cv

arXiv:2604.22834v1 Announce Type: new Abstract: This paper presents webmcu-vision-web, a single-file, zero-install browser application for end-to-end TinyML vision model training and deployment on the

Well-Conditioned Oblivious Perturbations in Linear Space

arXiv:2604.23193v1 Announce Type: cross Abstract: Perturbing a deterministic n-dimensional matrix with small Gaussian noise is a cornerstone of smoothed analysis of algorithms [Spielman and Teng, JACM

What Did They Mean? How LLMs Resolve Ambiguous Social Situations across Perspectives and Roles

arXiv:2604.23942v1 Announce Type: cross Abstract: People increasingly turn to large language models (LLMs) to interpret ambiguous social situations: a delayed text reply, an unusually cold supervisor,