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Towards Visual Query Localization in the 3D World

arXiv:2605.01498v1 Announce Type: new Abstract: Visual query localization (VQL) aims to predict the spatio-temporal response of the most recent occurrence in a sequence given a query. Currently, most

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TRACED: In vivo imaging of extracellular intrinsic diffusivity, tortuosity, cell size distribution and cell density in human glioma patients

DGX agent

arXiv:2605.02615v1 Announce Type: cross Abstract: The lack of analytical models describing diffusion time dependence at intermediate time scales in complex tissue microstructure limits the accurate qu

model-releasesarxiv-cs-lg

5 May 2026

Training-Free Adaptive 360-degree Video Streaming via Semantic Potential Fields

arXiv:2603.20999v2 Announce Type: replace-cross Abstract: Adaptive 360{eg} video streaming for teleoperation faces two coupled challenges: viewport prediction under uncertain gaze patterns and bitrate

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents

model-releasesarxiv-cs-ai

arXiv:2510.05950v2 Announce Type: replace Abstract: Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and in

Training Non-Differentiable Networks via Optimal Transport

arXiv:2605.01928v1 Announce Type: new Abstract: Neural networks increasingly embed non-differentiable components (spiking neurons, quantized layers, discrete routing, blackbox simulators, etc.) where

Tutorials

TrajRAG: Retrieving Geometric-Semantic Experience for Zero-Shot Object Navigation

arXiv:2605.01700v1 Announce Type: new Abstract: Existing zero-shot Object Goal Navigation (ObjectNav) methods often exploit commonsense knowledge from large language or vision-language models to guide

tutorialsarxiv-cs-cv

TrajShield: Trajectory-Level Safety Mediation for Defending Text-to-Video Models Against Jailbreak Attacks

arXiv:2605.01761v1 Announce Type: new Abstract: Text-to-Video (T2V) models have demonstrated remarkable capability in generating temporally coherent videos from natural language prompts, yet they also

Transfer Learning for Tonal Noise Prediction in VRF Units Using Thermodynamic and Vibration Signals

arXiv:2605.00895v1 Announce Type: cross Abstract: The second-order harmonic (2f) component generated by twin-rotary compressor is a dominant low-frequency noise source of variable refrigerant flow (VR

researcharxiv-cs-lg

TRAP: Tail-aware Ranking Attack for World-Model Planning

arXiv:2605.01950v1 Announce Type: new Abstract: World models enable long-horizon planning by internally generating and evaluating imagined trajectories, making them a promising foundation for generali

Trees and Graphs with Non Log-concave Dominating Set Sequence via AI Tools

arXiv:2605.02193v1 Announce Type: cross Abstract: We give new examples of graphs and trees with dominating set sequences that are not log-concave. These examples were generated by PatternBoost, a tran

researcharxiv-cs-lg

TRIM: A Self-Supervised Video Summarization Framework Maximizing Temporal Relative Information and Representativeness

arXiv:2506.20588v2 Announce Type: replace Abstract: The increasing ubiquity of video content and the corresponding demand for efficient access to meaningful information have elevated video summarizati

Applications

TRIMMER: A New Paradigm for Video Summarization through Self-Supervised Reinforcement Learning

arXiv:2605.01659v1 Announce Type: new Abstract: The rapid growth of video content across domains such as surveillance, education, and social media has made efficient content understanding increasingly

applicationsarxiv-cs-cv

TRIP-Evaluate: An Open Multimodal Benchmark for Evaluating Large Models in Transportation

arXiv:2605.00907v1 Announce Type: new Abstract: Large language models (LLMs) and multimodal large models (MLLMs) are increasingly used for transportation tasks such as regulation question answering, t

Triple Spectral Fusion for Sensor-based Human Activity Recognition

arXiv:2605.02743v1 Announce Type: cross Abstract: The field of sensor-based human activity recognition (HAR) mainly uses posture, motion and context data of Inertial Measurement Units (IMUs) to identi

Trust, but Verify: Peeling Low-Bit Transformer Networks for Training Monitoring

arXiv:2605.02853v1 Announce Type: new Abstract: Understanding whether deep neural networks are effectively optimized remains challenging, as training occurs in highly nonconvex landscapes and standard

local-aiarxiv-cs-lg

TT4D: A Pipeline and Dataset for Table Tennis 4D Reconstruction From Monocular Videos

arXiv:2605.01234v1 Announce Type: new Abstract: We present TT4D, a large-scale, high-fidelity table tennis dataset. It provides 140+ hours of reconstructed singles and doubles gameplay from monocular

TUR-DPO: Topology- and Uncertainty-Aware Direct Preference Optimization

arXiv:2605.00224v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human preferences is commonly done via reinforcement learning from human feedback (RLHF) with Proximal Policy

safetyarxiv-cs-ai

Turning Drift into Constraint: Robust Reasoning Alignment in Non-Stationary Environments

arXiv:2510.04142v2 Announce Type: replace Abstract: This paper identifies a critical yet underexplored challenge in reasoning alignment from multiple multi-modal large language models (MLLMs): In non-

TwistNet-2D: Learning Second-Order Channel Interactions via Spiral Twisting for Texture Recognition

arXiv:2602.07262v3 Announce Type: replace Abstract: Second-order feature statistics are central to texture recognition, yet existing mechanisms exhibit a structural tension: bilinear pooling and Gram

Two-Pass Zero-Shot Temporal-Spatial Grounding of Rare Traffic Events in Surveillance Video

arXiv:2605.01512v1 Announce Type: new Abstract: Grounding traffic accidents in real CCTV footage is a rare-event problem where training on labeled accident video is often prohibited, yet accurate join

Tutorials

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning

arXiv:2605.02765v1 Announce Type: cross Abstract: LLMs are increasingly used for end-user task planning, yet their black-box nature limits users' ability to ensure reliability and control. While recen

tutorialsarxiv-cs-lg

UCATSC: Uncertainty-Aware Constrained Traffic Signal Control Under Vision-Based Partial Observability

arXiv:2602.07784v3 Announce Type: replace Abstract: Camera-based adaptive traffic signal control is inherently partially observable: detections can be missed, vehicle speeds and distances can be noisy

Ultrafast On-chip Online Learning via Spline Locality in Kolmogorov-Arnold Networks

arXiv:2602.02056v2 Announce Type: replace-cross Abstract: Ultrafast online learning is essential for high-frequency systems, such as controls for quantum computing and nuclear fusion, where adaptation

local-aiarxiv-cs-lg

Ultrasound Vision-Language Alignment via Contrastive Learning

arXiv:2605.02126v1 Announce Type: new Abstract: Ultrasound foundation models have achieved strong performance on structured prediction tasks but remain exclusively vision-based, limiting zero-shot and

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

researcharxiv-cs-ai

Understanding Adversarial Imitation Learning in Small Sample Regime: A Stage-coupled Analysis

arXiv:2208.01899v2 Announce Type: replace Abstract: Imitation learning learns a policy from expert trajectories. While the expert data is believed to be crucial for imitation quality, it was found tha

Understanding Emergent Misalignment via Feature Superposition Geometry

model-releasesarxiv-cs-lg

arXiv:2605.00842v1 Announce Type: cross Abstract: Emergent misalignment, where fine-tuning on narrow, non-harmful tasks induces harmful behaviors, poses a key challenge for AI safety in LLMs. Despite

Understanding the Performance Plateau in Text-to-Video Retrieval: A Comprehensive Empirical and Linguistic Analysis

arXiv:2605.00826v1 Announce Type: cross Abstract: Text-to-video retrieval enables users to find relevant video content using natural language queries, a task that has grown increasingly important with

UnGAP: Uncertainty-Guided Affine Prompting for Real-Time Crack Segmentation

arXiv:2605.02380v1 Announce Type: new Abstract: Real-time crack segmentation is vital for structural health monitoring but is plagued by aleatoric uncertainties arising from varying lighting, blur, an

local-aiarxiv-cs-cv

Unified Map Prior Encoder for Mapping and Planning

arXiv:2605.02762v1 Announce Type: new Abstract: Online mapping and end-to-end (E2E) planning in autonomous driving remain largely sensor-centric, leaving rich map priors, including HD/SD vector maps,

Unifying Deep Stochastic Processes for Image Enhancement

arXiv:2605.01568v1 Announce Type: new Abstract: Deep stochastic processes have recently become a central paradigm for image enhancement, with many methods explicitly conditioning the stochastic trajec

Universality in Deep Neural Networks: An approach via the Lindeberg exchange principle

arXiv:2605.02771v1 Announce Type: cross Abstract: We consider the infinite-width limit of a fully connected deep neural network with general weights, and we prove quantitative general bounds on the 2-

researcharxiv-cs-lg

Unsupervised full-field Bayesian inference of orthotropic hyperelasticity from a single biaxial test: a myocardial case study

model-releasesarxiv-cs-lg

arXiv:2510.09498v3 Announce Type: replace-cross Abstract: Cardiac muscle tissue exhibits highly non-linear hyperelastic and orthotropic material behavior during passive deformation. Traditional consti

Unsupervised Learning of Robust Spectral Shape Matching

arXiv:2304.14419v2 Announce Type: replace Abstract: We propose a novel learning-based approach for robust 3D shape matching. Our method builds upon deep functional maps and can be trained in a fully u

Unsupervised Machine Learning for Detecting Structural Anomalies in European Regional Statistics

arXiv:2605.02884v1 Announce Type: new Abstract: Ensuring the coherence of regional socio-economic statistics is a central task for national statistical institutes. Traditional validation tools, such a

Validation of an AI-based end-to-end model for prostate pathology using long-term archived routine samples

arXiv:2605.02614v1 Announce Type: new Abstract: Artificial intelligence (AI) is becoming a clinical tool for prostate pathology, but generalization across variations in sample preparation and preserva

Validation of Whole-Slide Foundation Models for Image Retrieval in TCGA Data

arXiv:2605.00902v1 Announce Type: new Abstract: Foundation models are reshaping computational histopathology, yet their value for whole-slide image retrieval relative to strong patch-based and supervi

Value Functions for Temporal Logic: Optimal Policies and Safety Filters

arXiv:2605.01051v1 Announce Type: cross Abstract: While Bellman equations for basic reach, avoid, and reach-avoid problems are well studied, the relationship between value optimality and policy optima

Vanast: Virtual Try-On with Human Image Animation via Synthetic Triplet Supervision

arXiv:2604.04934v2 Announce Type: replace Abstract: We present Vanast, a unified framework that generates garment-transferred human animation videos directly from a single human image, garment images,

VAnim: Rendering-Aware Sparse State Modeling for Structure-Preserving Vector Animation

arXiv:2605.01517v1 Announce Type: new Abstract: Scalable Vector Graphics (SVG) animation generation is pivotal for professional design due to their structural editability and resolution independence.

Variational Matrix-Learning Fourier Networks for Parametric Multiphysics Surrogates

model-releasesarxiv-cs-lg

arXiv:2605.02280v1 Announce Type: new Abstract: Multiphysics simulation is critical for system-technology co-optimization (STCO) in chiplet-based design, but repeated finite-element solutions of PDE-g

Applications

VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation

arXiv:2602.21054v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) frequently hallucinate, limiting their safe deployment in real-world applications. Existing LLM self-eval

applicationsarxiv-cs-cl

Agents

Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning

arXiv:2605.01399v1 Announce Type: new Abstract: The conventional Retrieval-Augmented Generation (RAG) paradigm of injecting raw retrieved texts into the Large Language Model (LLM)'s context often resu

agentsarxiv-cs-cl

VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning

arXiv:2601.20055v2 Announce Type: replace Abstract: Despite the syntactic fluency of Large Language Models (LLMs), ensuring their logical correctness in high-stakes domains remains a fundamental chall

local-aiarxiv-cs-cl

VeRO: An Evaluation Harness for Agents to Optimize Agents

model-releasesarxiv-cs-cl

arXiv:2602.22480v2 Announce Type: replace-cross Abstract: An important emerging application of coding agents is agent optimization: the iterative improvement of a target agent through edit-execute-eva

Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration

arXiv:2509.10652v3 Announce Type: replace-cross Abstract: Generative AI is reshaping product design practices through 'vibe coding,' where product team members express intent in natural language and A

researcharxiv-cs-ai

Video Active Perception: Effective Inference-Time Long-Form Video Understanding with Vision-Language Models

arXiv:2605.01662v1 Announce Type: new Abstract: Large vision-language models (VLMs) have advanced multimodal tasks such as video question answering (QA). However, VLMs face the challenge of selecting

Tutorials

Video Generation with Predictive Latents

arXiv:2605.02134v1 Announce Type: new Abstract: Video Variational Autoencoder (VAE) enables latent video generative modeling by mapping the visual world into compact spatiotemporal latent spaces, impr

tutorialsarxiv-cs-cv