Unveiling Deep Shadows: A Survey and Benchmark on Image and Video Shadow Detection, Removal, and Generation in the Deep Learning Era


Unveiling Discrete Clues: Superior Healthcare Predictions for Rare Diseases


Unveiling Divergent Inductive Biases of LLMs on Temporal Data


Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit View


Unveiling Explosive Vulnerability of Networks through Edge Collective Behavior


Unveiling Factual Recall Behaviors of Large Language Models through Knowledge Neurons


Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction


Unveiling Gender Bias in Large Language Models: Using Teacher's Evaluation in Higher Education As an Example


Unveiling Global Interactive Patterns across Graphs: Towards Interpretable Graph Neural Networks


Unveiling Global Narratives: A Multilingual Twitter Dataset of News Media on the Russo-Ukrainian Conflict


Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning


Unveiling Hidden DNN Defects with Decision-Based Metamorphic Testing


Unveiling Implicit Table Knowledge with Question-Then-Pinpoint Reasoner for Insightful Table Summarization


Unveiling Interpretability in Self-Supervised Speech Representations for Parkinson's Diagnosis


Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph


Unveiling Language Skills via Path-Level Circuit Discovery


Unveiling Large Language Models Generated Texts: A Multi-Level Fine-Grained Detection Framework


Unveiling Linguistic Regions in Large Language Models


Unveiling Molecular Moieties through Hierarchical Grad-CAM Graph Explainability


Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property Prediction


Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses


Unveiling Pseudo-Crucial Events in Noise-Induced Phase Transitions


Unveiling Real-Life Effects of Online Photo Sharing


Unveiling Redundancy in Diffusion Transformers (DiTs): A Systematic Study


Unveiling Relations in the Industry 4.0 Standards Landscape based on Knowledge Graph Embeddings


Unveiling Topological Structures in Text: A Comprehensive Survey of Topological Data Analysis Applications in NLP


Unveiling Transformers with LEGO: a synthetic reasoning task


Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models


Unveiling User Preferences: A Knowledge Graph and LLM-Driven Approach for Conversational Recommendation


Unveiling Voices: A Co-Hashtag Analysis of TikTok Discourse on the 2023 Israel-Palestine Crisis


Unveiling Vulnerability of Self-Attention


Unveiling a young thick disk in the Milky Way


Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration


Unveiling and Manipulating Prompt Influence in Large Language Models


Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers


Unveiling and Mitigating Bias in Mental Health Analysis with Large Language Models


Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention


Unveiling and unraveling aggregation and dispersion fallacies in group MCDM


Unveiling interpretable development-specific gene signatures in the developing human prefrontal cortex with ICGS


Unveiling low-dimensional patterns induced by convex non-differentiable regularizers


Unveiling spatial patterns of population in Italian municipalities


Unveiling subarcsecond multiplicity in the Pleiades with Gaia multicolor photometry


Unveiling the Achilles' Heel of NLG Evaluators: A Unified Adversarial Framework Driven by Large Language Models


Unveiling the Compositional Ability Gap in Vision-Language Reasoning Model


Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression


Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming


Unveiling the Dynamics of Employee Behavior Through Wolframs Cellular Automata


Unveiling the Energy Vampires: A Methodology for Debugging Software Energy Consumption


Unveiling the Generalization Power of Fine-Tuned Large Language Models


Unveiling the Glass Veil: Elucidating the Optical Properties in Glasses with Interpretable Machine Learning


Unveiling the Hessian's Connection to the Decision Boundary


Unveiling the Hidden Structure of Self-Attention via Kernel Principal Component Analysis


Unveiling the Hidden: Movie Genre and User Bias in Spoiler Detection


Unveiling the Human-like Similarities of Automatic Facial Expression Recognition: An Empirical Exploration through Explainable AI


Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly


Unveiling the Impact of Multimodal Features on Chinese Spelling Correction: From Analysis to Design


Unveiling the Implicit Toxicity in Large Language Models


Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting


Unveiling the Invisible: Captioning Videos with Metaphors


Unveiling the Key Factors for Distilling Chain-of-Thought Reasoning


Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment


Unveiling the Mechanisms of DAI: A Logic-Based Approach to Stablecoin Analysis


Unveiling the Mechanisms of Explicit CoT Training: How CoT Enhances Reasoning Generalization


Unveiling the Mist over 3D Vision-Language Understanding: Object-centric Evaluation with Chain-of-Analysis


Unveiling the Mystery of Visual Attributes of Concrete and Abstract Concepts: Variability, Nearest Neighbors, and Challenging Categories


Unveiling the Pitfalls of Knowledge Editing for Large Language Models


Unveiling the Potential of AI for Nanomaterial Morphology Prediction


Unveiling the Potential of LLM-Based ASR on Chinese Open-Source Datasets


Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators


Unveiling the Potential of Segment Anything Model 2 for RGB-Thermal Semantic Segmentation with Language Guidance


Unveiling the Potential of Structure Preserving for Weakly Supervised Object Localization


Unveiling the Potential of Text in High-Dimensional Time Series Forecasting


Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling


Unveiling the Power of Self-supervision for Multi-view Multi-human Association and Tracking


Unveiling the Power of Sparse Neural Networks for Feature Selection


Unveiling the Safety of GPT-4o: An Empirical Study using Jailbreak Attacks


Unveiling the Secrets: How Masking Strategies Shape Time Series Imputation


Unveiling the Spectrum of Data Contamination in Language Models: A Survey from Detection to Remediation


Unveiling the Tapestry of Consistency in Large Vision-Language Models


Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks Against GNN-Based Fraud Detectors


Unveiling the Truth and Facilitating Change: Towards Agent-based Large-scale Social Movement Simulation


Unveiling the Truth: Exploring Human Gaze Patterns in Fake Images


Unveiling the Two-Faced Truth: Disentangling Morphed Identities for Face Morphing Detection


Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack


Unveiling the charge distribution of a GaAs-based nanoelectronic device: A large experimental data-set approach


Unveiling the drivers of the Baryon Cycles with Interpretable Multi-step Machine Learning and Simulations


Unveiling the hidden universe with JWST: The contribution of dust-obscured galaxies to the stellar mass function at $z\sim3-8$


Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be?


Unveiling the origin of fast radio bursts by modeling the stellar mass and star formation distributions of their host galaxies


Unveiling the potential of Graph Neural Networks for robust Intrusion Detection


Unveiling the rarest morphologies of the LOFAR Two-metre Sky Survey radio source population with self-organised maps


Unveiling the singular dynamics in the cosmic large-scale structure


Unveiling two types of local order in liquid water using machine learning


UoB at SemEval-2020 Task 1: Automatic Identification of Novel Word Senses


UoB at SemEval-2021 Task 5: Extending Pre-Trained Language Models to Include Task and Domain-Specific Information for Toxic Span Prediction


Uoc luong kenh truyen trong he thong da robot su dung SDR


Up to 100$\times$ Faster Data-free Knowledge Distillation


Up-sampling of electron beam simulation particles with addition of shot-noise


Up-to-date Threat Modelling for Soft Privacy on Smart Cars


UpStory: the Uppsala Storytelling dataset


Updatable Learned Index with Precise Positions


Update Your Transformer to the Latest Release: Re-Basin of Task Vectors


Updated Mutual Inclination Measurement for 14 Her b and c


Updated Transfer Coefficients for Magnetized Plasmas


Updated constraints on axion-like particles from temporal information in supernova SN1987A gamma-ray data


Updated implementation of next-to-leading order transversity evolution


Updating CLIP to Prefer Descriptions Over Captions


Updating Probabilistic Knowledge on Condition/Event Nets using Bayesian Networks


Updating Windows Malware Detectors: Balancing Robustness and Regression against Adversarial EXEmples


Updating the VESICLE-CNN Synapse Detector


Updating the generator in PPGN-h with gradients flowing through the encoder


Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver Segmentation


Upgrading Pepper Robot s Social Interaction with Advanced Hardware and Perception Enhancements


Uplift Modeling Under Limited Supervision


Uplift Modeling based on Graph Neural Network Combined with Causal Knowledge


Uplift Modeling for Target User Attacks on Recommender Systems


Uplift and Upsample: Efficient 3D Human Pose Estimation with Uplifting Transformers


Uplift modeling with continuous treatments: A predict-then-optimize approach


Uplift vs. predictive modeling: a theoretical analysis


Uplifting Lower-Income Data: Strategies for Socioeconomic Perspective Shifts in Large Multi-modal Models


Uplifting edges in higher order networks: spectral centralities for non-uniform hypergraphs


Upper Bounding Barlow Twins: A Novel Filter for Multi-Relational Clustering


Upper Limb Movement Recognition utilising EEG and EMG Signals for Rehabilitative Robotics


Upper bound for the number of spanning forests of regular graphs


Upper bounds on chromatic number of $\mathbb{E}^n$ in low dimensions


Upper limits on CN from exocomets transiting $β$ Pictoris


Upper-Body Pose-based Gaze Estimation for Privacy-Preserving 3D Gaze Target Detection


Upping the Ante: Towards a Better Benchmark for Chinese-to-English Machine Translation


Upsampling DINOv2 features for unsupervised vision tasks and weakly supervised materials segmentation


Upside Down Reinforcement Learning with Policy Generators


Upside down: affordable high-performance motion platform


Upside-Down Reinforcement Learning Can Diverge in Stochastic Environments With Episodic Resets


Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings


Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on Reddit


Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting


UrBench: A Comprehensive Benchmark for Evaluating Large Multimodal Models in Multi-View Urban Scenarios


UrFound: Towards Universal Retinal Foundation Models via Knowledge-Guided Masked Modeling


Urban Anomalies: A Simulated Human Mobility Dataset with Injected Anomalies


Urban Boundary Delineation from Commuting Data with Bayesian Stochastic Blockmodeling: Scale, Contiguity, and Hierarchy


Urban Change Detection Using a Dual-Task Siamese Network and Semi-Supervised Learning


Urban Computing in the Era of Large Language Models


Urban Delay Tolerant Network Simulator (UDTNSim v0.1)


Urban Driving with Multi-Objective Deep Reinforcement Learning


Urban Dynamics Through the Lens of Human Mobility


Urban Emergency Rescue Based on Multi-Agent Collaborative Learning: Coordination Between Fire Engines and Traffic Lights


Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment


Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports


Urban Pulse: Capturing the Rhythm of Cities


Urban Region Representation Learning with Attentive Fusion


Urban Rhapsody: Large-scale exploration of urban soundscapes


Urban Sound Classification : striving towards a fair comparison


Urban Sound Propagation: a Benchmark for 1-Step Generative Modeling of Complex Physical Systems


Urban Sound Tagging using Convolutional Neural Networks


Urban Traffic Accident Risk Prediction Revisited: Regionality, Proximity, Similarity and Sparsity


Urban Waterlogging Detection: A Challenging Benchmark and Large-Small Model Co-Adapter


Urban highways are barriers to social ties


Urban transport systems shape experiences of social segregation


Urban transportation networks and optimal transport-based infrastructures: similarity and economy of scale


Urban1960SatSeg: Unsupervised Semantic Segmentation of Mid-20$^{th}$ century Urban Landscapes with Satellite Imageries


UrbanDiT: A Foundation Model for Open-World Urban Spatio-Temporal Learning


UrbanFM: Inferring Fine-Grained Urban Flows


UrbanFly: Uncertainty-Aware Planning for Navigation Amongst High-Rises with Monocular Visual-Inertial SLAM Maps


UrbanGPT: Spatio-Temporal Large Language Models


UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction


UrbanVLP: Multi-Granularity Vision-Language Pretraining for Urban Socioeconomic Indicator Prediction


UrbanWorld: An Urban World Model for 3D City Generation


Urdu Word Segmentation using Conditional Random Fields (CRFs)


UrduFactCheck: An Agentic Fact-Checking Framework for Urdu with Evidence Boosting and Benchmarking


Urinary Tract Infection Detection in Digital Remote Monitoring: Strategies for Managing Participant-Specific Prediction Complexity


Urine Dataset having eight particles classes


UruDendro, a public dataset of cross-section images of Pinus taeda


Us vs. Them: A Dataset of Populist Attitudes, News Bias and Emotions


Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models


Usable Security for an IoT OS: Integrating the Zoo of Embedded Crypto Components Below a Common API


Use All The Labels: A Hierarchical Multi-Label Contrastive Learning Framework


Use Digital Twins to Support Fault Diagnosis From System-level Condition-monitoring Data


Use Perturbations when Learning from Explanations


Use QUDA for lattice QCD calculation with Python


Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification


Use Your Head: Improving Long-Tail Video Recognition


Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers


Use and abuse of instance parameters in the Lean mathematical library


Use of Air Quality Sensor Network Data for Real-time Pollution-Aware POI Suggestion


Use of Cryptography in Malware Obfuscation


Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population


Use of What-if Scenarios to Help Explain Artificial Intelligence Models for Neonatal Health


Use of a Structured Knowledge Base Enhances Metadata Curation by Large Language Models


Use of speaker recognition approaches for learning and evaluating embedding representations of musical instrument sounds


Use the Detection Transformer as a Data Augmenter


Useful Compact Representations for Data-Fitting


Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS'24 Experiment


User Behavior Retrieval for Click-Through Rate Prediction


User Behavior Simulation with Large Language Model based Agents


User Consented Federated Recommender System Against Personalized Attribute Inference Attack


User Customizable and Robust Geo-Indistinguishability for Location Privacy


User Diverse Preference Modeling by Multimodal Attentive Metric Learning


User Engagement Prediction for Clarification in Search


User Experience Design for Automatic Credibility Assessment of News Content About COVID-19


User Factor Adaptation for User Embedding via Multitask Learning


User Guide for KOTE: Korean Online Comments Emotions Dataset


User Intent Prediction in Information-seeking Conversations


User Migration across Multiple Social Media Platforms


User Modeling in the Era of Large Language Models: Current Research and Future Directions


User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction


User Retention-oriented Recommendation with Decision Transformer


User Satisfaction Estimation with Sequential Dialogue Act Modeling in Goal-oriented Conversational Systems


User Tracking in the Post-cookie Era: How Websites Bypass GDPR Consent to Track Users


User Training with Error Augmentation for Electromyogram-based Gesture Classification


User Willingness-aware Sales Talk Dataset


User manual for bch, a program for the fast computation of the Baker-Campbell-Hausdorff and similar series


User-Aware Folk Popularity Rank: User-Popularity-Based Tag Recommendation That Can Enhance Social Popularity


User-Centric Conversational Recommendation with Multi-Aspect User Modeling


User-Centric Perspective in Random Access Cell-Free Aided by Spatial Separability


User-Controllable Latent Transformer for StyleGAN Image Layout Editing


User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations


User-Dependent Neural Sequence Models for Continuous-Time Event Data


User-Entity Differential Privacy in Learning Natural Language Models


User-Friendly Customized Generation with Multi-Modal Prompts


User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization


User-Guided Aspect Classification for Domain-Specific Texts


User-Guided Clustering in Heterogeneous Information Networks via Motif-Based Comprehensive Transcription


User-Level Label Leakage from Gradients in Federated Learning


User-based representation of time-resolved multimodal public transportation networks


User-controllable Recommendation Against Filter Bubbles


User-guided Page Merging for Memory Deduplication in Serverless Systems


User-in-the-loop Adaptive Intent Detection for Instructable Digital Assistant


User-item fairness tradeoffs in recommendations


User-oriented Fairness in Recommendation


UserSimCRS: A User Simulation Toolkit for Evaluating Conversational Recommender Systems


Userfault Objects: Transparent Programmable Memory


Username Squatting on Online Social Networks: A Study on X


Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video


Using A One-Class SVM To Optimize Transit Detection


Using AGN lightcurves to map accretion disc temperature fluctuations


Using AI Large Language Models for Grading in Education: A Hands-On Test for Physics


Using AI to Summarize US Presidential Campaign TV Advertisement Videos, 1952-2012


Using Adapters to Overcome Catastrophic Forgetting in End-to-End Automatic Speech Recognition


Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health


Using Adaptive Empathetic Responses for Teaching English


Using Affect as a Communication Modality to Improve Human-Robot Communication in Robot-Assisted Search and Rescue Scenarios


Using Amazon Alexa APIs as a Source of Digital Evidence


Using Artificial Populations to Study Psychological Phenomena in Neural Models


Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection


Using BERT Encoding to Tackle the Mad-lib Attack in SMS Spam Detection


Using Bayesian deep learning approaches for uncertainty-aware building energy surrogate models


Using BibTeX to Automatically Generate Labeled Data for Citation Field Extraction


Using Biot-Savart boundary conditions for unbounded external flow on Eulerian meshes


Using Bottleneck Adapters to Identify Cancer in Clinical Notes under Low-Resource Constraints


Using C++ to Calculate $\mathsf{SO(10)}$ Tensor Couplings


Using Case Description Information to Reduce Sensitivity to Bias for the Attributable Fraction Among the Exposed


Using Cell Phone Pictures of Sheet Music To Retrieve MIDI Passages


Using ChatGPT as a CAT tool in Easy Language translation


Using Chinese Glyphs for Named Entity Recognition


Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions


Using Clinical Notes with Time Series Data for ICU Management


Using Colors to Improve Photometric Metallicity Estimates for Galaxies


Using Conditional Generative Adversarial Networks to Reduce the Effects of Latency in Robotic Telesurgery


Using Conformal Win Probability to Predict the Winners of the Cancelled 2020 NCAA Basketball Tournaments


Using Consensual Biterms from Text Structures of Requirements and Code to Improve IR-Based Traceability Recovery


Using Constraint Programming and Graph Representation Learning for Generating Interpretable Cloud Security Policies


Using Constraints to Discover Sparse and Alternative Subgroup Descriptions


Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings


Using Curiosity for an Even Representation of Tasks in Continual Offline Reinforcement Learning


Using DUCK-Net for Polyp Image Segmentation


Using Database Dependencies to Constrain Approval-Based Committee Voting in the Presence of Context


Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME


Using Decoupled Features for Photo-realistic Style Transfer


Using Deep Convolutional Neural Networks to Diagnose COVID-19 From Chest X-Ray Images


Using Deep LSD to build operators in GANs latent space with meaning in real space


Using Deep Learning for Segmentation and Counting within Microscopy Data


Using Deep Learning for Title-Based Semantic Subject Indexing to Reach Competitive Performance to Full-Text


Using Deep Learning to Design High Aspect Ratio Fusion Devices


Using Deep Learning to Extend the Range of Air-Pollution Monitoring and Forecasting


Using Deep Learning to Generate Complete Log Statements


Using Deep Learning to Identify Initial Error Sensitivity for Interpretable ENSO Forecasts


Using Deep Neural Networks to Predict and Improve the Performance of Polar Codes


Using Deep Neural Networks to compute the mass of forming planets


Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics


Using Developer Discussions to Guide Fixing Bugs in Software


Using Differentiable Programming for Flexible Statistical Modeling


Using Diffusion Models to Generate Synthetic Labelled Data for Medical Image Segmentation


Using Dimensionality Reduction to Optimize t-SNE


Using Discourse Signals for Robust Instructor Intervention Prediction


Using Distributed Representations to Disambiguate Biomedical and Clinical Concepts


Using Echo-State Networks to Reproduce Rare Events in Chaotic Systems


Using Elasticsearch for entity recognition in affiliation disambiguation


Using Embeddings to Correct for Unobserved Confounding in Networks


Using Exact Tests from Algebraic Statistics in Sparse Multi-way Analyses: An Application to Analyzing Differential Item Functioning


Using Explainability to Inform Statistical Downscaling Based on Deep Learning Beyond Standard Validation Approaches


Using Explainable AI and Transfer Learning to understand and predict the maintenance of Atlantic blocking with limited observational data


Using Explainable AI for EEG-based Reduced Montage Neonatal Seizure Detection


Using Eye-tracking Data to Predict Situation Awareness in Real Time during Takeover Transitions in Conditionally Automated Driving


Using Facebook Ads Audiences for Global Lifestyle Disease Surveillance: Promises and Limitations


Using Feature Alignment Can Improve Clean Average Precision and Adversarial Robustness in Object Detection


Using Finite-State Machines to Automatically Scan Classical Greek Hexameter


Using Fitness Dependent Optimizer for Training Multi-layer Perceptron


Using Fitts' Law to Benchmark Assisted Human-Robot Performance


Using Focal Loss to Fight Shallow Heuristics: An Empirical Analysis of Modulated Cross-Entropy in Natural Language Inference


Using GAMA to probe the impact of small-scale galaxy physics on nonlinear redshift-space distortions


Using GNN property predictors as molecule generators


Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models


Using Gaussian Boson Samplers to Approximate Gaussian Expectation Problems


Using Generative Agents to Create Tip Sheets for Investigative Data Reporting


Using Geographic Location-based Public Health Features in Survival Analysis


Using Google Trends as a proxy for occupant behavior to predict building energy consumption


Using Graph Neural Networks and Frequency Domain Data for Automated Operational Modal Analysis of Populations of Structures


Using Hand Pose Estimation To Automate Open Surgery Training Feedback


Using Hashtags to Analyze Purpose and Technology Application of Open-Source Project Related to COVID-19


Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model


Using Instruction-Tuned Large Language Models to Identify Indicators of Vulnerability in Police Incident Narratives


Using Instruments for Selection to Adjust for Selection Bias in Mendelian Randomization


Using Interaction Data to Predict Engagement with Interactive Media


Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment


Using Intermarket Data to Evaluate the Efficient Market Hypothesis with Machine Learning


Using Inverse Optimization to Learn Cost Functions in Generalized Nash Games


Using Knowledge Graphs to harvest datasets for efficient CLIP model training


Using Knowledge-Embedded Attention to Augment Pre-trained Language Models for Fine-Grained Emotion Recognition


Using LLM such as ChatGPT for Designing and Implementing a RISC Processor: Execution,Challenges and Limitations


Using LLMs for Explaining Sets of Counterfactual Examples to Final Users


Using LLMs for Security Advisory Investigations: How Far Are We?


Using LLMs for the Extraction and Normalization of Product Attribute Values


Using LLMs in Generating Design Rationale for Software Architecture Decisions


Using LLMs to Investigate Correlations of Conversational Follow-up Queries with User Satisfaction


Using LLMs to label medical papers according to the CIViC evidence model


Using LSST Microlensing to Constrain Dark Compact Objects in Spherical and Disk Configurations


Using LSTM and SARIMA Models to Forecast Cluster CPU Usage


Using LSTM for the Prediction of Disruption in ADITYA Tokamak


Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes


Using Language Models to Disambiguate Lexical Choices in Translation


Using Language to Extend to Unseen Domains


Using Large Language Models for Hyperparameter Optimization


Using Large Language Models for Knowledge Engineering (LLMKE): A Case Study on Wikidata


Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science Education


Using Large Language Models for Template Detection from Security Event Logs


Using Large Language Models for Zero-Shot Natural Language Generation from Knowledge Graphs


Using Large Language Models to Generate JUnit Tests: An Empirical Study


Using Large Language Models to Tackle Fundamental Challenges in Graph Learning: A Comprehensive Survey


Using Large Multimodal Models to Extract Knowledge Components for Knowledge Tracing from Multimedia Question Information


Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler


Using Linguistic Features to Improve the Generalization Capability of Neural Coreference Resolvers


Using Linguistic Typology to Enrich Multilingual Lexicons: the Case of Lexical Gaps in Kinship


Using Linked Micromaps for Evidence-Based Policy


Using Localized Twitter Activity for Red Tide Impact Assessment


Using Low-rank Representation of Abundance Maps and Nonnegative Tensor Factorization for Hyperspectral Nonlinear Unmixing


Using MM principles to deal with incomplete data in K-means clustering


Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks


Using Machine Learning to Detect Rotational Symmetries from Reflectional Symmetries in 2D Images


Using Machine Learning to Determine Morphologies of $z<1$ AGN Host Galaxies in the Hyper Suprime-Cam Wide Survey


Using Machine Learning to Emulate Agent-Based Simulations


Using Machine Learning to Fuse Verbal Autopsy Narratives and Binary Features in the Analysis of Deaths from Hyperglycaemia


Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis


Using Machine Learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan Region


Using Markov transition matrices to generate trial configurations in Markov chain Monte Carlo simulations


Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models


Using Meta-learning to Recommend Process Discovery Methods


Using Micro-collections in Social Media to Generate Seeds for Web Archive Collections


Using Microbenchmark Suites to Detect Application Performance Changes


Using Mobility for Electrical Load Forecasting During the COVID-19 Pandemic


Using Monte Carlo Tree Search to Calculate Mutual Information in High Dimensions


Using Motif Transitions for Temporal Graph Generation


Using Motion Forecasting for Behavior-Based Virtual Reality (VR) Authentication


Using Multi-Label Classification for Improved Question Answering


Using Multi-Sense Vector Embeddings for Reverse Dictionaries


Using Multiple Imputation to Classify Potential Outcomes Subgroups


Using Multiple Instance Learning for Explainable Solar Flare Prediction


Using Multiple Self-Supervised Tasks Improves Model Robustness


Using Natural Language Explanations to Improve Robustness of In-context Learning


Using Natural Language Explanations to Rescale Human Judgments


Using Natural Language Relations between Answer Choices for Machine Comprehension


Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines


Using Natural Sentences for Understanding Biases in Language Models


Using Neural Networks for Fast SAR Roughness Estimation of High Resolution Images


Using Neutrino Oscillations to Measure $H_0$


Using Offline Data to Speed Up Reinforcement Learning in Procedurally Generated Environments


Using Online Customer Reviews to Classify, Predict, and Learn about Domestic Robot Failures


Using Orientation to Distinguish Overlapping Chromosomes


Using Overlap Weights to Address Extreme Propensity Scores in Estimating Restricted Mean Counterfactual Survival Times


Using PPP Information to Implement a Global Real-Time Virtual Network DGNSS Approach


Using Panoramic Videos for Multi-person Localization and Tracking in a 3D Panoramic Coordinate


Using Particle Swarm Optimization as Pathfinding Strategy in a Space with Obstacles


Using Persistent Homology Topological Features to Characterize Medical Images: Case Studies on Lung and Brain Cancers


Using Personality Detection Tools for Software Engineering Research: How Far Can We Go?


Using Persuasive Writing Strategies to Explain and Detect Health Misinformation


Using Perturbation to Improve Goodness-of-Fit Tests based on Kernelized Stein Discrepancy


Using Phonemes in cascaded S2S translation pipeline


Using Physics Informed Neural Networks for Supernova Radiative Transfer Simulation


Using Pilot Systems to Execute Many Task Workloads on Supercomputers


Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario


Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding Networks for Image Compressive Sensing


Using Pre-Trained Models to Boost Code Review Automation


Using Pre-Training Can Improve Model Robustness and Uncertainty


Using Pre-training and Interaction Modeling for ancestry-specific disease prediction in UK Biobank


Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models


Using Prior Knowledge to Guide BERT's Attention in Semantic Textual Matching Tasks


Using Probabilistic Machine Learning to Better Model Temporal Patterns in Parameterizations: a case study with the Lorenz 96 model


Using Proxy Pattern-Mixture Models to Explain Bias in Estimates of COVID-19 Vaccine Uptake from Two Large Surveys


Using Punkt for Sentence Segmentation in non-Latin Scripts: Experiments on Kurdish (Sorani) Texts


Using Quantum Annealers to Calculate Ground State Properties of Molecules


Using Quantum Computers to Speed Up Dynamic Testing of Software


Using Query Expansion in Manifold Ranking for Query-Oriented Multi-Document Summarization


Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users


Using Reed-Muller Codes for Classification with Rejection and Recovery


Using Reinforcement Learning for Load Testing of Video Games


Using Reinforcement Learning in the Algorithmic Trading Problem


Using Reinforcement Learning to Perform Qubit Routing in Quantum Compilers


Using Restricted Boltzmann Machines to Model Molecular Geometries


Using SMT Solvers to Validate Models for AI Problems


Using SVM to pre-classify government purchases


Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees


Using Satellite Imagery and Deep Learning to Evaluate the Impact of Anti-Poverty Programs


Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge


Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty


Using Self-supervised Learning Can Improve Model Fairness


Using Semantic Similarity for Input Topic Identification in Crawling-based Web Application Testing


Using Sentence Embeddings and Semantic Similarity for Seeking Consensus when Assessing Trustworthy AI


Using Sentiment Induction to Understand Variation in Gendered Online Communities


Using Set Covering to Generate Databases for Holistic Steganalysis


Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features


Using Similarity Measures to Select Pretraining Data for NER


Using Simple Incentives to Improve Two-Sided Fairness in Ridesharing Systems


Using Simulation Optimization to Improve Zero-shot Policy Transfer of Quadrotors


Using Small MUSes to Explain How to Solve Pen and Paper Puzzles


Using Socially Expressive Mixed Reality Arms for Enhancing Low-Expressivity Robots


Using Soft Actor-Critic for Low-Level UAV Control


Using Software Product Lines to Create Blockchain Products: Application to Supply Chain Traceability


Using Solar Orbiter as an upstream solar wind monitor for real time space weather predictions


Using Source Code Density to Improve the Accuracy of Automatic Commit Classification into Maintenance Activities


Using Source-Side Confidence Estimation for Reliable Translation into Unfamiliar Languages


Using Space-Filling Curves and Fractals to Reveal Spatial and Temporal Patterns in Neuroimaging Data


Using Spherical Harmonics to solve the Boltzmann equation: an operator based approach


Using Standard Typing Algorithms Incrementally


Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning


Using Stratified Sampling to Improve LIME Image Explanations


Using Structural and Semantic Information to Identify Software Components


Using Style Ambiguity Loss to Improve Aesthetics of Diffusion Models


Using Subjective Logic to Estimate Uncertainty in Multi-Armed Bandit Problems


Using Symbolic Computation to Analyze Zero-Hopf Bifurcations of Polynomial Differential Systems


Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types


Using Syntax to Ground Referring Expressions in Natural Images


Using Synthetic Corruptions to Measure Robustness to Natural Distribution Shifts


Using Synthetic Data to Enhance the Accuracy of Fingerprint-Based Localization: A Deep Learning Approach


Using Temperature Sensitivity to Estimate Shiftable Electricity Demand: Implications for power system investments and climate change


Using Text Embeddings for Deductive Qualitative Research at Scale in Physics Education


Using The Polynomial Particle-In-Cell Method For Liquid-Fabric Interaction


Using Think-Aloud Data to Understand Relations between Self-Regulation Cycle Characteristics and Student Performance in Intelligent Tutoring Systems


Using Time Structure to Estimate Causal Effects


Using Time-Aware Graph Neural Networks to Predict Temporal Centralities in Dynamic Graphs


Using Time-Series Privileged Information for Provably Efficient Learning of Prediction Models


Using Titles vs. Full-text as Source for Automated Semantic Document Annotation


Using Transfer Learning for Code-Related Tasks


Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise


Using Twitter Data to Understand Public Perceptions of Approved versus Off-label Use for COVID-19-related Medications


Using Twitter to Analyze Political Polarization During National Crises


Using UMAP to Inspect Audio Data for Unsupervised Anomaly Detection under Domain-Shift Conditions


Using Uncertainty Quantification to Characterize and Improve Out-of-Domain Learning for PDEs


Using Under-trained Deep Ensembles to Learn Under Extreme Label Noise


Using Unsupervised Learning to Help Discover the Causal Graph


Using VAEs to Learn Latent Variables: Observations on Applications in cryo-EM


Using Variable Natural Environment Brain-Computer Interface Stimuli for Real-time Humanoid Robot Navigation


Using Visual Anomaly Detection for Task Execution Monitoring


Using Vivado-HLS for Structural Design: a NoC Case Study


Using Word Embeddings to Examine Gender Bias in Dutch Newspapers, 1950-1990


Using Z3 for Formal Modeling and Verification of FNN Global Robustness


Using Zigzag Persistent Homology to Detect Hopf Bifurcations in Dynamical Systems


Using a Fast Adaptive Function Approximator to calculate Protein-Filament Binding Kinetics


Using a Feedback Loop for LLM-based Infrastructure as Code Generation


Using a KG-Copy Network for Non-Goal Oriented Dialogues


Using a Novel COVID-19 Calculator to Measure Positive U.S. Socio-Economic Impact of a COVID-19 Pre-Screening Solution (AI/ML)


Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery


Using a Waffle Iron for Automotive Point Cloud Semantic Segmentation


Using a negative spatial auto-correlation index to evaluate and improve intrinsic TagMap's multi-scale visualization capabilities


Using a neural network approach to accelerate disequilibrium chemistry calculations in exoplanet atmospheres


Using a one dimensional parabolic model of the full-batch loss to estimate learning rates during training


Using a one-dimensional finite-element approximation of Webster's horn equation to estimate individual ear canal acoustic transfer from input impedances


Using altmetrics for detecting impactful research in quasi-zero-day time-windows: the case of COVID-19


Using birth-death processes to infer tumor subpopulation structure from live-cell imaging drug screening data


Using cGANs for Anomaly Detection: Identifying Astronomical Anomalies in JWST NIRcam Imaging


Using causal inference and Bayesian statistics to explain the capability of a test suite in exposing software faults


Using coarse GPS data to quantify city-scale transportation system resilience to extreme events


Using convolutional neural networks for the classification of breast cancer images


Using convolutional neural networks to predict galaxy metallicity from three-color images


Using deep generative neural networks to account for model errors in Markov chain Monte Carlo inversion


Using deep learning to construct stochastic local search SAT solvers with performance bounds


Using directed acyclic graphs to determine whether multiple imputation or subsample multiple imputation estimates of an exposure-outcome association are unbiased


Using dynamic loss weighting to boost improvements in forecast stability


Using early rejection Markov chain Monte Carlo and Gaussian processes to accelerate ABC methods


Using explainable AI to investigate electrocardiogram changes during healthy aging -- from expert features to raw signals


Using eye tracking to investigate what native Chinese speakers notice about linguistic landscape images


Using generative modelling to produce varied intonation for speech synthesis


Using genotype abundance to improve phylogenetic inference


Using human and robot synthetic data for training smart hand tools


Using in-situ solar-wind observations to generate inner-boundary conditions to outer-heliosphere simulations, 1: Dynamic time warping applied to synthetic observations


Using joint training speaker encoder with consistency loss to achieve cross-lingual voice conversion and expressive voice conversion


Using linear initialisation to improve speed of convergence and fully-trained error in Autoencoders


Using link and content over time for embedding generation in Dynamic Attributed Networks


Using machine learning on new feature sets extracted from 3D models of broken animal bones to classify fragments according to break agent


Using machine learning to compress the matter transfer function $T(k)$


Using machine learning to inform harvest control rule design in complex fishery settings


Using machine learning to understand causal relationships between urban form and travel CO2 emissions across continents


Using mixup as regularization and tuning hyper-parameters for ResNets


Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic in England


Using multi-delay discrete delay differential equations to accurately simulate models with distributed delays


Using musical relationships between chord labels in automatic chord extraction tasks


Using natural language processing techniques to extract information on the properties and functionalities of energetic materials from large text corpora


Using network structure and community detection to discover important website features when distinguishing between phishing and legitimate ones


Using neural networks for efficient evaluation of high multiplicity scattering amplitudes


Using neural networks to estimate redshift distributions. An application to CFHTLenS


Using neural networks to model Main Belt Asteroid albedos as a function of their proper orbital elements


Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations


Using noise resilience for ranking generalization of deep neural networks


Using optical tweezer electrophoresis to investigate clay nanoplatelet adsorption on Latex microspheres in aqueous media


Using optimal control to guide neural-network interpolation of continuously-parameterized gates


Using peculiar velocity surveys to constrain neutrino masses


Using peculiar velocity surveys to constrain the growth rate of structure with the wide-angle effect


Using phase instead of optical flow for action recognition


Using photoelectron spectroscopy to measure resonant inelastic X-ray scattering: A computational investigation


Using physics-based simulation towards eliminating empiricism in extraterrestrial terramechanics applications


Using physics-informed neural networks to compute quasinormal modes


Using power system modelling outputs to identify weather-induced extreme events in highly renewable systems


Using prior information to boost power in correlation structure support recovery


Using quantum computers in control: interval matrix properties


Using reinforcement learning to improve drone-based inference of greenhouse gas fluxes


Using relativistic effects in large-scale structure to constrain astrophysical properties of galaxy populations


Using representation balancing to learn conditional-average dose responses from clustered data


Using second-order information in gradient sampling methods for nonsmooth optimization


Using shrinkage methods to estimate treatment effects in overlapping subgroups in randomized clinical trials with a time-to-event endpoint


Using simulated annealing for locating array construction


Using smartphone photographs of the Moon to acquaint students with non-Euclidean geometry


Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example


Using stigmergy as a computational memory in the design of recurrent neural networks


Using stigmergy to incorporate the time into artificial neural networks


Using stochastic computation graphs formalism for optimization of sequence-to-sequence model


Using the GP2X framework for center-of-mass energy precision studies at $e^+e^-$ Higgs factories


Using the Gaia excess uncertainty as a proxy for stellar variability and age


Using the Output Embedding to Improve Language Models


Using the Path of Least Resistance to Explain Deep Networks


Using the Prognostic Score to Reduce Heterogeneity in Observational Studies


Using the SourceXtractor++ package for data reduction


Using the profile of publishers to predict barriers across news articles


Using theory-driven Integrated Population Models to evaluate competitive outcomes in stage-structured systems


Using topological autoencoders as a filtering function for global and local topology


Using tours to visually investigate properties of new projection pursuit indexes with application to problems in physics


Using unsupervised learning to detect broken symmetries, with relevance to searches for parity violation in nature. (Previously: "Stressed GANs snag desserts")


Utilising Deep Learning Techniques for Effective Zero-Day Attack Detection


Utilising Deep Learning to Elicit Expert Uncertainty


Utilising a Quantum Hybrid Solver for Bi-objective Quadratic Assignment Problems


Utilising physics-guided deep learning to overcome data scarcity


Utility AI for Dynamic Task Offloading in the Multi-Edge Infrastructure


Utility Assessment of Synthetic Data Generation Methods


Utility of Equivariant Message Passing in Cortical Mesh Segmentation


Utility-Based Context-Aware Multi-Agent Recommendation System for Energy Efficiency in Residential Buildings


Utility-based Adaptive Teaching Strategies using Bayesian Theory of Mind


Utility-based Resource Allocation and Pricing for Serverless Computing


Utility/Privacy Trade-off through the lens of Optimal Transport


Utilize the Flow before Stepping into the Same River Twice: Certainty Represented Knowledge Flow for Refusal-Aware Instruction Tuning


Utilizing Background Knowledge for Robust Reasoning over Traffic Situations


Utilizing Bidirectional Encoder Representations from Transformers for Answer Selection


Utilizing Class Information for Deep Network Representation Shaping


Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasets


Utilizing Description Logics for Global Explanations of Heterogeneous Graph Neural Networks


Utilizing Domain Knowledge in End-to-End Audio Processing


Utilizing Evolution Strategies to Train Transformers in Reinforcement Learning


Utilizing Expert Features for Contrastive Learning of Time-Series Representations


Utilizing Explainability Techniques for Reinforcement Learning Model Assurance


Utilizing FastText for Venue Recommendation


Utilizing Generative Adversarial Networks for Stable Structure Generation in Angry Birds


Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment


Utilizing Local Hierarchy with Adversarial Training for Hierarchical Text Classification


Utilizing Longitudinal Chest X-Rays and Reports to Pre-Fill Radiology Reports


Utilizing Lyapunov Exponents in designing deep neural networks


Utilizing Machine Learning to Predict Host Stars and the Key Elemental Abundances of Small Planets


Utilizing Multi-step Loss for Single Image Reflection Removal


Utilizing Public Blockchains for the Sybil-Resistant Bootstrapping of Distributed Anonymity Services


Utilizing RNN for Real-time Cryptocurrency Price Prediction and Trading Strategy Optimization


Utilizing Reinforcement Learning for de novo Drug Design


Utilizing Semantic Textual Similarity for Clinical Survey Data Feature Selection


Utilizing Source Code Syntax Patterns to Detect Bug Inducing Commits using Machine Learning Models


Utilizing Synthetic Data for Medical Vision-Language Pre-training: Bypassing the Need for Real Images


Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking


Utilizing Treewidth for Quantitative Reasoning on Epistemic Logic Programs


Utilizing Uncertainty in 2D Pose Detectors for Probabilistic 3D Human Mesh Recovery


Utilizing WaveFunctionCollapse Algorithm for Procedural Generation of Terrains using Remotely Sensed Elevation Data


Utilizing a Capture-Recapture Strategy to Accelerate Infectious Disease Surveillance


Utilizing a null class to restrict decision spaces and defend against neural network adversarial attacks


Utilizing geospatial data for assessing energy security: Mapping small solar home systems using unmanned aerial vehicles and deep learning


Utopia: Fast and Efficient Address Translation via Hybrid Restrictive & Flexible Virtual-to-Physical Address Mappings


Utterance Weighted Multi-Dilation Temporal Convolutional Networks for Monaural Speech Dereverberation


Utterance-to-Utterance Interactive Matching Network for Multi-Turn Response Selection in Retrieval-Based Chatbots


V$^2$L: Leveraging Vision and Vision-language Models into Large-scale Product Retrieval


V-, U-, L-, or W-shaped economic recovery after COVID: Insights from an Agent Based Model


V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection


V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization


V-EfficientNets: Vector-Valued Efficiently Scaled Convolutional Neural Network Models


V-FUSE: Volumetric Depth Map Fusion with Long-Range Constraints


V-Guard: An Efficient Permissioned Blockchain for Achieving Consensus under Dynamic Memberships in V2X


V-IRL: Grounding Virtual Intelligence in Real Life


V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning


V-LoL: A Diagnostic Dataset for Visual Logical Learning


V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models


V-Max: A Reinforcement Learning Framework for Autonomous Driving


V-NAW: Video-based Noise-aware Adaptive Weighting for Facial Expression Recognition


V-PRISM: Probabilistic Mapping of Unknown Tabletop Scenes


V-RECS, a Low-Cost LLM4VIS Recommender with Explanations, Captioning and Suggestions


V-RoAst: Visual Road Assessment. Can VLM be a Road Safety Assessor Using the iRAP Standard?


V-Shaped Sparse Arrays For 2-D DOA Estimation


V-Zen: Efficient GUI Understanding and Precise Grounding With A Novel Multimodal LLM


V2: Fast Detection of Configuration Drift in Python


V2A-Mapper: A Lightweight Solution for Vision-to-Audio Generation by Connecting Foundation Models


V2C-CBM: Building Concept Bottlenecks with Vision-to-Concept Tokenizer


V2Flow: Unifying Visual Tokenization and Large Language Model Vocabularies for Autoregressive Image Generation


V2M: Visual 2-Dimensional Mamba for Image Representation Learning


V2P-Bench: Evaluating Video-Language Understanding with Visual Prompts for Better Human-Model Interaction


V2PE: Improving Multimodal Long-Context Capability of Vision-Language Models with Variable Visual Position Encoding


V2T-CoT: From Vision to Text Chain-of-Thought for Medical Reasoning and Diagnosis


V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perception


V2V: Scaling Event-Based Vision through Efficient Video-to-Voxel Simulation


V2W-BERT: A Framework for Effective Hierarchical Multiclass Classification of Software Vulnerabilities


V2X-AHD:Vehicle-to-Everything Cooperation Perception via Asymmetric Heterogenous Distillation Network


V2X-Assisted Distributed Computing and Control Framework for Connected and Automated Vehicles under Ramp Merging Scenario


V2X-DGPE: Addressing Domain Gaps and Pose Errors for Robust Collaborative 3D Object Detection


V2X-R: Cooperative LiDAR-4D Radar Fusion for 3D Object Detection with Denoising Diffusion


V2X-Seq: A Large-Scale Sequential Dataset for Vehicle-Infrastructure Cooperative Perception and Forecasting


V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer


V2XP-ASG: Generating Adversarial Scenes for Vehicle-to-Everything Perception


V2XPnP: Vehicle-to-Everything Spatio-Temporal Fusion for Multi-Agent Perception and Prediction


V3D-SLAM: Robust RGB-D SLAM in Dynamic Environments with 3D Semantic Geometry Voting


V3D: Video Diffusion Models are Effective 3D Generators


V3H: View Variation and View Heredity for Incomplete Multi-view Clustering


VA3: Virtually Assured Amplification Attack on Probabilistic Copyright Protection for Text-to-Image Generative Models


VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries


VADA: a Data-Driven Simulator for Nanopore Sequencing


VADER: A Flexible, Robust, Open-Source Code for Simulating Viscous Thin Accretion Disks


VADER: A Human-Evaluated Benchmark for Vulnerability Assessment, Detection, Explanation, and Remediation


VADIS -- a VAriable Detection, Interlinking and Summarization system


VADMamba: Exploring State Space Models for Fast Video Anomaly Detection


VAE-CE: Visual Contrastive Explanation using Disentangled VAEs


VAE-based Phoneme Alignment Using Gradient Annealing and SSL Acoustic Features


VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming


VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data


VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis


VAESim: A probabilistic approach for self-supervised prototype discovery


VAEmo: Efficient Representation Learning for Visual-Audio Emotion with Knowledge Injection


VALE: A Multimodal Visual and Language Explanation Framework for Image Classifiers using eXplainable AI and Language Models


VALID: A perceptually validated Virtual Avatar Library for Inclusion and Diversity


VALO: A Versatile Anytime Framework for LiDAR-based Object Detection Deep Neural Networks


VALOR-EVAL: Holistic Coverage and Faithfulness Evaluation of Large Vision-Language Models


VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena


VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation


VALUE: Understanding Dialect Disparity in NLU


VALVEFIT: An analysis-suitable B-spline-based surface fitting framework for patient-specific modeling of tricuspid valves


VAMPnets: Deep learning of molecular kinetics


VAMPyR -- A High-Level Python Library for Mathematical Operations in a Multiwavelets Representation


VANP: Learning Where to See for Navigation with Self-Supervised Vision-Action Pre-Training


VANiLLa : Verbalized Answers in Natural Language at Large Scale


VAPOR: Legged Robot Navigation in Outdoor Vegetation Using Offline Reinforcement Learning


VAR-CLIP: Text-to-Image Generator with Visual Auto-Regressive Modeling


VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge


VARFVV: View-Adaptive Real-Time Interactive Free-View Video Streaming with Edge Computing


VARX Granger Analysis: Modeling, Inference, and Applications


VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI


VASP2KP: kp models and Lande g-factors from ab initio calculations


VASPKIT: A User-friendly Interface Facilitating High-throughput Computing and Analysis Using VASP Code


VASR: Visual Analogies of Situation Recognition


VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset


VAST: The Valence-Assessing Semantics Test for Contextualizing Language Models


VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuning


VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media


VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks


VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions


VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models


VC dimension of Graph Neural Networks with Pfaffian activation functions


VC dimension of partially quantized neural networks in the overparametrized regime


VCAT: Vulnerability-aware and Curiosity-driven Adversarial Training for Enhancing Autonomous Vehicle Robustness


VCBART: Bayesian trees for varying coefficients


VCD: A Video Conferencing Dataset for Video Compression


VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition Modeling


VCG Under False-name Attacks: a Bayesian Analysis


VCGAN: Video Colorization with Hybrid Generative Adversarial Network


VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic Data


VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments


VCNet: A self-explaining model for realistic counterfactual generation


VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation


VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections


VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text


VCR: Video representation for Contextual Retrieval


VCRBench: Exploring Long-form Causal Reasoning Capabilities of Large Video Language Models


VCSUM: A Versatile Chinese Meeting Summarization Dataset


VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D Annotations


VCWE: Visual Character-Enhanced Word Embeddings


VCapsBench: A Large-scale Fine-grained Benchmark for Video Caption Quality Evaluation


VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting


VCoder: Versatile Vision Encoders for Multimodal Large Language Models


VD-BERT: A Unified Vision and Dialog Transformer with BERT


VD-PCR: Improving Visual Dialog with Pronoun Coreference Resolution


VDB-EDT: An Efficient Euclidean Distance Transform Algorithm Based on VDB Data Structure


VDB-GPDF: Online Gaussian Process Distance Field with VDB Structure


VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models


VDD: Varied Drone Dataset for Semantic Segmentation


VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations


VDMS: Efficient Big-Visual-Data Access for Machine Learning Workloads


VDN-NeRF: Resolving Shape-Radiance Ambiguity via View-Dependence Normalization


VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of Experts


VDT: General-purpose Video Diffusion Transformers via Mask Modeling


VDTuner: Automated Performance Tuning for Vector Data Management Systems


VDebugger: Harnessing Execution Feedback for Debugging Visual Programs


VE: Modeling Multivariate Time Series Correlation with Variate Embedding


VEAttack: Downstream-agnostic Vision Encoder Attack against Large Vision Language Models


VEC-SBM: Optimal Community Detection with Vectorial Edges Covariates


VECHR: A Dataset for Explainable and Robust Classification of Vulnerability Type in the European Court of Human Rights


VECSR: Virtually Embodied Common Sense Reasoning System


VECT-GAN: A variationally encoded generative model for overcoming data scarcity in pharmaceutical science


VECTOR: Velocity-Enhanced GRU Neural Network for Real-Time 3D UAV Trajectory Prediction


VEDA: Uneven light image enhancement via a vision-based exploratory data analysis model


VEGAS: Towards Visually Explainable and Grounded Artificial Social Intelligence


VEGS: View Extrapolation of Urban Scenes in 3D Gaussian Splatting using Learned Priors


VELMA: Verbalization Embodiment of LLM Agents for Vision and Language Navigation in Street View


VELVET: a noVel Ensemble Learning approach to automatically locate VulnErable sTatements


VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition


VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification


VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores


VENOM: Text-driven Unrestricted Adversarial Example Generation with Diffusion Models


VER: Unifying Verbalizing Entities and Relations


VERA: Generating Visual Explanations of Two-Dimensional Embeddings via Region Annotation


VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations


VERIFIED: A Video Corpus Moment Retrieval Benchmark for Fine-Grained Video Understanding


VERINA: Benchmarking Verifiable Code Generation


VERISCORE: Evaluating the factuality of verifiable claims in long-form text generation


VERITAS-NLI : Validation and Extraction of Reliable Information Through Automated Scraping and Natural Language Inference


VERITAS: Verification and Explanation of Realness in Images for Transparency in AI Systems


VERITE: A Robust Benchmark for Multimodal Misinformation Detection Accounting for Unimodal Bias


VERSE: Versatile Graph Embeddings from Similarity Measures


VERTECS: A COTS-based payload interface board to enable next generation astronomical imaging payloads


VERTICO VII: Environmental quenching caused by suppression of molecular gas content and star formation efficiency in Virgo Cluster galaxies


VESPo: Verified Evaluation of Secret Polynomials


VET: Identifying and Avoiding UI Exploration Tarpits


VET: Visual Error Tomography for Point Cloud Completion and High-Quality Neural Rendering


VEXIR2Vec: An Architecture-Neutral Embedding Framework for Binary Similarity


VEglue: Testing Visual Entailment Systems via Object-Aligned Joint Erasing


VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videos


VF-NeRF: Learning Neural Vector Fields for Indoor Scene Reconstruction


VFCFinder: Seamlessly Pairing Security Advisories and Patches


VFH+ based shared control for remotely operated mobile robots


VFIMamba: Video Frame Interpolation with State Space Models


VFLAIR: A Research Library and Benchmark for Vertical Federated Learning


VFLGAN: Vertical Federated Learning-based Generative Adversarial Network for Vertically Partitioned Data Publication


VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification


VFM-Det: Towards High-Performance Vehicle Detection via Large Foundation Models


VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals


VFlow: More Expressive Generative Flows with Variational Data Augmentation


VG-SSL: Benchmarking Self-supervised Representation Learning Approaches for Visual Geo-localization


VG-TVP: Multimodal Procedural Planning via Visually Grounded Text-Video Prompting


VG4D: Vision-Language Model Goes 4D Video Recognition


VGA: Vision GUI Assistant -- Minimizing Hallucinations through Image-Centric Fine-Tuning


VGAER: Graph Neural Network Reconstruction based Community Detection


VGAT: A Cancer Survival Analysis Framework Transitioning from Generative Visual Question Answering to Genomic Reconstruction


VGBench: Evaluating Large Language Models on Vector Graphics Understanding and Generation


VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification


VGDFR: Diffusion-based Video Generation with Dynamic Latent Frame Rate


VGDiffZero: Text-to-image Diffusion Models Can Be Zero-shot Visual Grounders


VGGHeads: 3D Multi Head Alignment with a Large-Scale Synthetic Dataset


VGGT: Visual Geometry Grounded Transformer


VGLD: Visually-Guided Linguistic Disambiguation for Monocular Depth Scale Recovery


VGMShield: Mitigating Misuse of Video Generative Models


VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs


VGSE: Visually-Grounded Semantic Embeddings for Zero-Shot Learning


VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph


VHASR: A Multimodal Speech Recognition System With Vision Hotwords


VI-Diff: Unpaired Visible-Infrared Translation Diffusion Model for Single Modality Labeled Visible-Infrared Person Re-identification


VI-Net: Boosting Category-level 6D Object Pose Estimation via Learning Decoupled Rotations on the Spherical Representations


VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution Detection


VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern Recognition


VIBE: Video-to-Text Information Bottleneck Evaluation for TL;DR


VIBIKNet: Visual Bidirectional Kernelized Network for Visual Question Answering


VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum Modeling


VICCA: Visual Interpretation and Comprehension of Chest X-ray Anomalies in Generated Report Without Human Feedback


VICE: Variational Interpretable Concept Embeddings


VICEROY: GDPR-/CCPA-compliant Enforcement of Verifiable Accountless Consumer Requests


VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction


VICTOR: Visual Incompatibility Detection with Transformers and Fashion-specific contrastive pre-training


VICatMix: variational Bayesian clustering and variable selection for discrete biomedical data


VID-Fusion: Robust Visual-Inertial-Dynamics Odometry for Accurate External Force Estimation


VID-WIN: Fast Video Event Matching with Query-Aware Windowing at the Edge for the Internet of Multimedia Things


VIDA: A simulation model of domestic VIolence in times of social DistAncing


VIDEX: A Disaggregated and Extensible Virtual Index for the Cloud and AI Era


VIDSTAMP: A Temporally-Aware Watermark for Ownership and Integrity in Video Diffusion Models


VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation


VIFNet: An End-to-end Visible-Infrared Fusion Network for Image Dehazing


VIFS: An End-to-End Variational Inference for Foley Sound Synthesis


VIGAN: Missing View Imputation with Generative Adversarial Networks


VIGFace: Virtual Identity Generation for Privacy-Free Face Recognition


VIGMA: An Open-Access Framework for Visual Gait and Motion Analytics


VIGNETTE: Socially Grounded Bias Evaluation for Vision-Language Models


VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval


VIIS: Visible and Infrared Information Synthesis for Severe Low-light Image Enhancement


VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection


VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation


VILA: Improving Structured Content Extraction from Scientific PDFs Using Visual Layout Groups


VILP: Imitation Learning with Latent Video Planning


VIMA: General Robot Manipulation with Multimodal Prompts


VIMU: Effective Physics-based Realtime Detection and Recovery against Stealthy Attacks on UAVs


VINE: Visualizing Statistical Interactions in Black Box Models


VINNA for Neonates -- Orientation Independence through Latent Augmentations


VINP: Variational Bayesian Inference with Neural Speech Prior for Joint ASR-Effective Speech Dereverberation and Blind RIR Identification


VIODE: A Simulated Dataset to Address the Challenges of Visual-Inertial Odometry in Dynamic Environments


VIOLET : End-to-End Video-Language Transformers with Masked Visual-token Modeling


VIOLIN: A Large-Scale Dataset for Video-and-Language Inference


VIP -- Variational Inversion Package with example implementations of Bayesian tomographic imaging


VIP5: Towards Multimodal Foundation Models for Recommendation


VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training


VIP: Versatile Image Outpainting Empowered by Multimodal Large Language Model


VIP: Visual Information Protection through Adversarial Attacks on Vision-Language Models


VIP: Vortex Image Processing package for high-contrast direct imaging


VIPHY: Probing "Visible" Physical Commonsense Knowledge


VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation


VIPriors 1: Visual Inductive Priors for Data-Efficient Deep Learning Challenges


VIRAL: Vision-grounded Integration for Reward design And Learning


VIRD: Immersive Match Video Analysis for High-Performance Badminton Coaching


VIRDO: Visio-tactile Implicit Representations of Deformable Objects


VIREL: A Variational Inference Framework for Reinforcement Learning


VIRIS: Simulating indoor airborne transmission combining architectural design and people movement


VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability Estimation


VIRUS-NeRF -- Vision, InfraRed and UltraSonic based Neural Radiance Fields


VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification


VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generation


VISA: An Ambiguous Subtitles Dataset for Visual Scene-Aware Machine Translation


VISEM-Tracking, a human spermatozoa tracking dataset


VISER: A Tractable Solution Concept for Games with Information Asymmetry


VISION: A Modular AI Assistant for Natural Human-Instrument Interaction at Scientific User Facilities


VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator


VISOLO: Grid-Based Space-Time Aggregation for Efficient Online Video Instance Segmentation


VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions


VISTA-SSM: Varying and Irregular Sampling Time-series Analysis via State Space Models


VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention


VISTA: Vision Transformer enhanced by U-Net and Image Colorfulness Frame Filtration for Automatic Retail Checkout


VISTANet: VIsual Spoken Textual Additive Net for Interpretable Multimodal Emotion Recognition


VITA-Audio: Fast Interleaved Cross-Modal Token Generation for Efficient Large Speech-Language Model


VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation


VITA: A Multi-modal LLM-based System for Longitudinal, Autonomous, and Adaptive Robotic Mental Well-being Coaching


VITA: Video Instance Segmentation via Object Token Association


VITAL: More Understandable Feature Visualization through Distribution Alignment and Relevant Information Flow


VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models


VITON-DRR: Details Retention Virtual Try-on via Non-rigid Registration


VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization


VIoLET: A Large-scale Virtual Environment for Internet of Things


VIoTGPT: Learning to Schedule Vision Tools in LLMs towards Intelligent Video Internet of Things


VJAGG -- A Thick-Client Smart-Phone Journey Detection Algorithm


VKFPos: A Learning-Based Monocular Positioning with Variational Bayesian Extended Kalman Filter Integration


VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks


VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations


VL-GLUE: A Suite of Fundamental yet Challenging Visuo-Linguistic Reasoning Tasks


VL-GPT: A Generative Pre-trained Transformer for Vision and Language Understanding and Generation


VL-Grasp: a 6-Dof Interactive Grasp Policy for Language-Oriented Objects in Cluttered Indoor Scenes


VL-ICL Bench: The Devil in the Details of Multimodal In-Context Learning


VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition


VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control


VL-SAT: Visual-Linguistic Semantics Assisted Training for 3D Semantic Scene Graph Prediction in Point Cloud


VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models


VLA monitoring of LS V +44 17 reveals scatter in the X-ray--radio correlation of Be/X-ray binaries


VLA-3D: A Dataset for 3D Semantic Scene Understanding and Navigation


VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning


VLAD-VSA: Cross-Domain Face Presentation Attack Detection with Vocabulary Separation and Adaptation


VLAS: Vision-Language-Action Model With Speech Instructions For Customized Robot Manipulation


VLBI Celestial and Terrestrial Reference Frames VIE2022b


VLBI Network SIMulator: An Integrated Simulation Tool for Radio Astronomers


VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model


VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge


VLCap: Vision-Language with Contrastive Learning for Coherent Video Paragraph Captioning


VLCounter: Text-aware Visual Representation for Zero-Shot Object Counting


VLEU: a Method for Automatic Evaluation for Generalizability of Text-to-Image Models


VLFM: Vision-Language Frontier Maps for Zero-Shot Semantic Navigation


VLG: General Video Recognition with Web Textual Knowledge


VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark


VLLMs Provide Better Context for Emotion Understanding Through Common Sense Reasoning


VLLaVO: Mitigating Visual Gap through LLMs


VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction


VLM-Auto: VLM-based Autonomous Driving Assistant with Human-like Behavior and Understanding for Complex Road Scenes


VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Human Annotation-Free Pathological Image Classification


VLM-Grounder: A VLM Agent for Zero-Shot 3D Visual Grounding


VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model


VLM-driven Behavior Tree for Context-aware Task Planning


VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images


VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts


VLMs Can Aggregate Scattered Training Patches


VLMs as GeoGuessr Masters: Exceptional Performance, Hidden Biases, and Privacy Risks


VLN-PETL: Parameter-Efficient Transfer Learning for Vision-and-Language Navigation


VLP: A Survey on Vision-Language Pre-training


VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision


VLPrompt: Vision-Language Prompting for Panoptic Scene Graph Generation


VLRMBench: A Comprehensive and Challenging Benchmark for Vision-Language Reward Models


VLSBench: Unveiling Visual Leakage in Multimodal Safety


VLSI Designs for Joint Channel Estimation and Data Detection in Large SIMO Wireless Systems


VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blocks


VLSNR:Vision-Linguistics Coordination Time Sequence-aware News Recommendation


VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene Completion


VLSlice: Interactive Vision-and-Language Slice Discovery


VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation


VLTinT: Visual-Linguistic Transformer-in-Transformer for Coherent Video Paragraph Captioning


VLUE: A Multi-Task Benchmark for Evaluating Vision-Language Models


VLind-Bench: Measuring Language Priors in Large Vision-Language Models


VLog: Video-Language Models by Generative Retrieval of Narration Vocabulary


VM-NeRF: Tackling Sparsity in NeRF with View Morphing


VM-Rec: A Variational Mapping Approach for Cold-start User Recommendation


VM-UNet: Vision Mamba UNet for Medical Image Segmentation


VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene


VMBench: A Benchmark for Perception-Aligned Video Motion Generation


VMC Optimization of Ultra-Compact, Explicitly-Correlated Wave Functions of the Li Isoelectronic Sequence in Its Lowest 1s2s2p Quartet State


VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models


VME: A Satellite Imagery Dataset and Benchmark for Detecting Vehicles in the Middle East and Beyond


VMEXT: A Visualization Tool for Mathematical Expression Trees


VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization


VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation


VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction


VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting


VMSMO: Learning to Generate Multimodal Summary for Video-based News Articles


VMT19937: A SIMD-Friendly Pseudo Random Number Generator based on Mersenne Twister 19937


VMTS: Vision-Assisted Teacher-Student Reinforcement Learning for Multi-Terrain Locomotion in Bipedal Robots


VMix: Improving Text-to-Image Diffusion Model with Cross-Attention Mixing Control


VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution


VNHSGE: VietNamese High School Graduation Examination Dataset for Large Language Models


VNIbCReg: VICReg with Neighboring-Invariance and better-Covariance Evaluated on Non-stationary Seismic Signal Time Series


VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees


VOC-ReID: Vehicle Re-identification based on Vehicle-Orientation-Camera


VOICE: Variance of Induced Contrastive Explanations to quantify Uncertainty in Neural Network Interpretability


VOILA: Complexity-Aware Universal Segmentation of CT images by Voxel Interacting with Language


VOLKS2: a transient search and localization pipeline for VLBI observations


VOLoc: Visual Place Recognition by Querying Compressed Lidar Map


VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE


VOOM: Robust Visual Object Odometry and Mapping using Hierarchical Landmarks


VOPy: A Framework for Black-box Vector Optimization


VORTA: Efficient Video Diffusion via Routing Sparse Attention


VORTEX: Challenging CNNs at Texture Recognition by using Vision Transformers with Orderless and Randomized Token Encodings


VOS: Learning What You Don't Know by Virtual Outlier Synthesis


VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting


VPAIR -- Aerial Visual Place Recognition and Localization in Large-scale Outdoor Environments


VPC-Net: Completion of 3D Vehicles from MLS Point Clouds


VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition


VPGS-SLAM: Voxel-based Progressive 3D Gaussian SLAM in Large-Scale Scenes


VPGTrans: Transfer Visual Prompt Generator across LLMs


VPI-Bench: Visual Prompt Injection Attacks for Computer-Use Agents


VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images


VPN++: Rethinking Video-Pose embeddings for understanding Activities of Daily Living


VPN: Learning Video-Pose Embedding for Activities of Daily Living


VPNets: Volume-preserving neural networks for learning source-free dynamics


VPO: Aligning Text-to-Video Generation Models with Prompt Optimization


VPO: Leveraging the Number of Votes in Preference Optimization


VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models


VPVet: Vetting Privacy Policies of Virtual Reality Apps


VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution Reasoning


VQ-Flow: Taming Normalizing Flows for Multi-Class Anomaly Detection via Hierarchical Vector Quantization


VQ-Font: Few-Shot Font Generation with Structure-Aware Enhancement and Quantization


VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization


VQ-Map: Bird's-Eye-View Map Layout Estimation in Tokenized Discrete Space via Vector Quantization


VQ-NeRV: A Vector Quantized Neural Representation for Videos


VQA Therapy: Exploring Answer Differences by Visually Grounding Answers


VQA$^2$: Visual Question Answering for Video Quality Assessment


VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering


VQC-Based Reinforcement Learning with Data Re-uploading: Performance and Trainability


VQCNIR: Clearer Night Image Restoration with Vector-Quantized Codebook


VQCPC-GAN: Variable-Length Adversarial Audio Synthesis Using Vector-Quantized Contrastive Predictive Coding


VQE-generated Quantum Circuit Dataset for Machine Learning


VQF: Highly Accurate IMU Orientation Estimation with Bias Estimation and Magnetic Disturbance Rejection


VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder


VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance


VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs


VQLTI: Long-Term Tropical Cyclone Intensity Forecasting with Physical Constraints


VQMIVC: Vector Quantization and Mutual Information-Based Unsupervised Speech Representation Disentanglement for One-shot Voice Conversion


VQPy: An Object-Oriented Approach to Modern Video Analytics


VQVC+: One-Shot Voice Conversion by Vector Quantization and U-Net architecture


VR Sickness Prediction from Integrated HMD's Sensors using Multimodal Deep Fusion Network


VR Viewport Pose Model for Quantifying and Exploiting Frame Correlations


VR-SGD: A Simple Stochastic Variance Reduction Method for Machine Learning


VR3Dense: Voxel Representation Learning for 3D Object Detection and Monocular Dense Depth Reconstruction


VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning


VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning


VRHCF: Cross-Source Point Cloud Registration via Voxel Representation and Hierarchical Correspondence Filtering


VRKG4Rec: Virtual Relational Knowledge Graphs for Recommendation


VRKitchen: an Interactive 3D Virtual Environment for Task-oriented Learning


VRMDiff: Text-Guided Video Referring Matting Generation of Diffusion


VRMN-bD: A Multi-modal Natural Behavior Dataset of Immersive Human Fear Responses in VR Stand-up Interactive Games


VRMenuDesigner: A toolkit for automatically generating and modifying VR menus


VRP-SAM: SAM with Visual Reference Prompt


VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field


VRSO: Visual-Centric Reconstruction for Static Object Annotation


VRSplat: Fast and Robust Gaussian Splatting for Virtual Reality


VReST: Enhancing Reasoning in Large Vision-Language Models through Tree Search and Self-Reward Mechanism


VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Text


VRoPE: Rotary Position Embedding for Video Large Language Models


VS-Net: Variable splitting network for accelerated parallel MRI reconstruction


VS-Net: Voting with Segmentation for Visual Localization


VSA: Learning Varied-Size Window Attention in Vision Transformers


VSC-WebGPU: A Selenium-based VS Code Extension For Local Edit And Cloud Compilation on WebGPU


VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration


VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning


VSFormer: Mining Correlations in Flexible View Set for Multi-view 3D Shape Understanding


VSFormer: Visual-Spatial Fusion Transformer for Correspondence Pruning


VSGM -- Enhance robot task understanding ability through visual semantic graph


VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions


VSLAM-LAB: A Comprehensive Framework for Visual SLAM Methods and Datasets


VSP: Assessing the dual challenges of perception and reasoning in spatial planning tasks for VLMs


VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object Detection


VSSD: Vision Mamba with Non-Causal State Space Duality


VST-Pose: A Velocity-Integrated Spatiotem-poral Attention Network for Human WiFi Pose Estimation


VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions


VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis


VStreamDRLS: Dynamic Graph Representation Learning with Self-Attention for Enterprise Distributed Video Streaming Solutions


VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization


VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization


VTAE: Variational Transformer Autoencoder with Manifolds Learning


VTAMIQ: Transformers for Attention Modulated Image Quality Assessment


VTBench: Comprehensive Benchmark Suite Towards Real-World Virtual Try-on Models


VTBench: Evaluating Visual Tokenizers for Autoregressive Image Generation


VTG-GPT: Tuning-Free Zero-Shot Video Temporal Grounding with GPT


VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding


VTGNet: A Vision-based Trajectory Generation Network for Autonomous Vehicles in Urban Environments


VTON-IT: Virtual Try-On using Image Translation


VTQA: Visual Text Question Answering via Entity Alignment and Cross-Media Reasoning


VTS-LLM: Domain-Adaptive LLM Agent for Enhancing Awareness in Vessel Traffic Services through Natural Language


VTimeLLM: Empower LLM to Grasp Video Moments


VToonify: Controllable High-Resolution Portrait Video Style Transfer


VURF: A General-purpose Reasoning and Self-refinement Framework for Video Understanding


VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection


VV-Net: Voxel VAE Net with Group Convolutions for Point Cloud Segmentation


VVS: Video-to-Video Retrieval with Irrelevant Frame Suppression


VWAP Execution with Signature-Enhanced Transformers: A Multi-Asset Learning Approach


VXP: Voxel-Cross-Pixel Large-scale Image-LiDAR Place Recognition


VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding


VaLiPro: Linear Programming Validator for Cluster Computing Systems


VaN3Twin: the Multi-Technology V2X Digital Twin with Ray-Tracing in the Loop


VaPar Synth -- A Variational Parametric Model for Audio Synthesis


VaTEST III: Validation of 8 Potential Super-Earths from TESS Data


VacHopPy: A Python package for vacancy hopping analysis based on ab initio molecular dynamics simulations


VacSIM: Learning Effective Strategies for COVID-19 Vaccine Distribution using Reinforcement Learning


VacancySBERT: the approach for representation of titles and skills for semantic similarity search in the recruitment domain


VaccinEU: COVID-19 vaccine conversations on Twitter in French, German and Italian


VaccinItaly: monitoring Italian conversations around vaccines on Twitter and Facebook


Vaccination dynamics of age-structured populations in higher-order social networks


Vaccine Discourse on Twitter During the COVID-19 Pandemic


Vaccine allocation policy optimization and budget sharing mechanism using Thompson sampling


Vaccine skepticism detection by network embedding


Vacuum structure of the left-right symmetric model


VacuumTunneling: A package to solve bounce equation with renormalization factor


Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought


VadCLIP: Adapting Vision-Language Models for Weakly Supervised Video Anomaly Detection


VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level Relation Extraction


Vagus nerve stimulation: Laying the groundwork for predictive network-based computer models


Vahana.jl -- A framework (not only) for large-scale agent-based models


VaiPhy: a Variational Inference Based Algorithm for Phylogeny


ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation


Valentine: Evaluating Matching Techniques for Dataset Discovery


Valeo4Cast: A Modular Approach to End-to-End Forecasting


ValiText -- a unified validation framework for computational text-based measures of social constructs


Valid Bootstraps for Network Embeddings with Applications to Network Visualisation


Valid Conformal Prediction for Dynamic GNNs


Valid Inference Corrected for Outlier Removal


Valid Inference for Machine Learning Model Parameters


Valid Two-Sample Graph Testing via Optimal Transport Procrustes and Multiscale Graph Correlation with Applications in Connectomics


Valid belief updates for prequentially additive loss functions arising in Semi-Modular Inference


Valid causal inference with unobserved confounding in high-dimensional settings


Valid inequalities and a branch-and-cut algorithm for the routing and spectrum allocation problem


Valid prediction intervals for regression problems


Valid predictions of random quantities in linear mixed models


Valid sequential inference on probability forecast performance


Validated Numerical Approximation of Stable Manifolds for Parabolic Partial Differential Equations


Validated enclosure of renormalization fixed points via Chebyshev series and the DFT


Validated error bounds for pseudospectral approximation of delay differential equations: unstable manifolds


Validated integration of semilinear parabolic PDEs


Validated matrix multiplication transform for orthogonal polynomials with applications to computer-assisted proofs for PDEs


Validated spectral stability via conjugate points


Validating Clustering Frameworks for Electric Load Demand Profiles


Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events


Validating GWAS Findings through Reverse Engineering of Contingency Tables


Validating Labelled State Transition and Message Production Systems: A Theory for Modelling Faulty Distributed Systems


Validating Large Language Models with ReLM


Validating Large-Scale Quantum Machine Learning: Efficient Simulation of Quantum Support Vector Machines Using Tensor Networks


Validating Prior-informed Fisher-matrix Analyses against GWTC Data


Validating Quantum-Classical Programming Models with Tensor Network Simulations


Validating Simulations of User Query Variants


Validating Synthetic Usage Data in Living Lab Environments


Validating full-spectrum fitting with a synthetic integral-field spectroscopic observation of the Milky Way


Validation and Comparison of Non-Stationary Cognitive Models: A Diffusion Model Application


Validation of Abstract Side-Channel Models for Computer Architectures


Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations


Validation of Gaia DR3 orbital and acceleration solutions with hierarchical triples


Validation of Inventory models for Single-echelon Supply Chain using Discrete-event Simulation


Validation of ML-UQ calibration statistics using simulated reference values: a sensitivity analysis


Validation of Modern JSON Schema: Formalization and Complexity


Validation of a Zero-Shot Learning Natural Language Processing Tool for Data Abstraction from Unstructured Healthcare Data


Validation of non-negative matrix factorization for assessment of atomic pair-distribution function (PDF) data in a real-time streaming context


Validation of open-source science tools and background model construction in $γ$-ray astronomy


Validation of point process predictions with proper scoring rules


Validation of the Alchemical Transfer Method for the Estimation of Relative Binding Affinities of Molecular Series


Validation of the Bond et al. (2010) SDSS-derived kinematic models for the Milky Way's disk and halo stars with Gaia Data Release 3 proper motion and radial velocity data


Validation of uncertainty quantification metrics: a primer based on the consistency and adaptivity concepts


Validations and Corrections of the SFD and Planck Reddening Maps Based on LAMOST and Gaia Data


Validity Assessment of Legal Will Statements as Natural Language Inference


Validity of Markovian modeling for transient memory-dependent epidemic dynamics


Validity of contextual formulas (extended version)


Validity problems in clinical machine learning by indirect data labeling using consensus definitions


Validity-first automatic polycube labeling for CAD models


Valkyrie: A Response Framework to Augment Runtime Detection of Time-Progressive Attacks


Valley: Video Assistant with Large Language model Enhanced abilitY


Value Activation for Bias Alleviation: Generalized-activated Deep Double Deterministic Policy Gradients


Value Approximation for Two-Player General-Sum Differential Games with State Constraints


Value Augmented Sampling for Language Model Alignment and Personalization


Value Function Based Difference-of-Convex Algorithm for Bilevel Hyperparameter Selection Problems


Value Functions are Control Barrier Functions: Verification of Safe Policies using Control Theory


Value Gradient Sampler: Sampling as Sequential Decision Making


Value Gradient weighted Model-Based Reinforcement Learning


Value Internalization: Learning and Generalizing from Social Reward


Value Iteration Networks on Multiple Levels of Abstraction


Value Iteration for Learning Concurrently Executable Robotic Control Tasks


Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties


Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning


Value Residual Learning For Alleviating Attention Concentration In Transformers


Value Sliced and Derivative Images for Source Mask in JWST MIRI Photometry


Value function approximation via low-rank models


Value of risk-contact data from digital contact monitoring apps in infectious disease modeling


Value-Distributional Model-Based Reinforcement Learning


Value-Enriched Population Synthesis: Integrating a Motivational Layer


Value-Free Policy Optimization via Reward Partitioning


Value-Function-based Sequential Minimization for Bi-level Optimization


Value-Gradient Iteration with Quadratic Approximate Value Functions


Value-Guided Search for Efficient Chain-of-Thought Reasoning


Value-Informed Skill Chaining for Policy Learning of Long-Horizon Tasks with Surgical Robot


Value-based Resource Matching with Fairness Criteria: Application to Agricultural Water Trading


ValueBench: Towards Comprehensively Evaluating Value Orientations and Understanding of Large Language Models


ValueDCG: Measuring Comprehensive Human Value Understanding Ability of Language Models


ValueScope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactions


Values That Are Explicitly Present in Fairy Tales: Comparing Samples from German, Italian and Portuguese Traditions


Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathology


Vamos: Versatile Action Models for Video Understanding


VampNet: Music Generation via Masked Acoustic Token Modeling


Vandal: A Scalable Security Analysis Framework for Smart Contracts


Vanilla Gradient Descent for Oblique Decision Trees


Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image Encoders


Vanishing Gradients in Reinforcement Finetuning of Language Models


Vanishing Point Estimation in Uncalibrated Images with Prior Gravity Direction


Vanishing Stacked-Residual PINN for State Reconstruction of Hyperbolic Systems


Vanishing properties of Kloosterman sums and Dyson's conjectures


Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes


VapoRock: Thermodynamics of vaporized silicate melts for modeling volcanic outgassing and magma ocean atmospheres


VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling


VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation


VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning


VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting


VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPS


VarGrad: A Low-Variance Gradient Estimator for Variational Inference


VarNet: Variational Neural Networks for the Solution of Partial Differential Equations


VarRCWA: An Adaptive High-Order Rigorous Coupled Wave Analysis Method


VarSaw: Application-tailored Measurement Error Mitigation for Variational Quantum Algorithms


VarStar Detect, a Python library dedicated to the semi-automatic detection of stellar variability


Varaha: A promising sampler for obtaining gravitational wave posteriors


VariTex: Variational Neural Face Textures


Variability Modeling of Products, Processes, and Resources in Cyber-Physical Production Systems Engineering


Variability in Footpoint Mapping of BBFs Using Tsyganenko Models: Impact on Swarm Conjunctions


Variability in higher order structure of noise added to weighted networks


Variability in the local and global composition of human T-cell receptor repertoires during thymic development across cell types and individuals


Variable Assignment Invariant Neural Networks for Learning Logic Programs


Variable Importance Matching for Causal Inference


Variable Importance in High-Dimensional Settings Requires Grouping


Variable Order Fractional Fokker-Planck Equations derived from Continuous Time Random Walks


Variable Rate Compression for Raw 3D Point Clouds


Variable Rate Learned Wavelet Video Coding using Temporal Layer Adaptivity


Variable Rate Neural Compression for Sparse Detector Data


Variable Selection Using Bayesian Additive Regression Trees


Variable Selection and Regularization via Arbitrary Rectangle-range Generalized Elastic Net


Variable Selection and Task Grouping for Multi-Task Learning


Variable Selection for Multiply-imputed Data: A Bayesian Framework


Variable Selection in Functional Linear Concurrent Regression


Variable Selection in GLM and Cox Models with Second-Generation P-Values


Variable Selection in High Dimensional Linear Regressions with Parameter Instability


Variable Selection with Second-Generation P-Values


Variable Skipping for Autoregressive Range Density Estimation