Search: “applications”

PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting

arXiv:2508.04750v2 Announce Type: replace Abstract: In real-world applications, multimodal time-series forecasting faces a key challenge: textual information is often useful but unreliable. Auxiliary

12 May 2026

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Applications

TrajDLM: Topology-Aware Block Diffusion Language Model for Trajectory Generation

DGX agent

arXiv:2605.10020v1 Announce Type: new Abstract: Generating high-fidelity synthetic GPS trajectories is increasingly important for applications in transportation, urban planning, and what-if scenario s

applicationsarxiv-cs-lg

12 May 2026

Integrating Causal DAGs in Deep RL: Activating Minimal Markovian States with Multi-Order Exposure

arXiv:2605.07057v1 Announce Type: new Abstract: Online reinforcement learning (RL) relies on the Markov property for guaranteed performance, but real-world applications often lack well-defined states

11 May 2026

Offline-Online Hierarchical 3D Global Relocalization With Synthetic LiDAR Sensing and Descriptor-Space Retrieval

arXiv:2605.07741v1 Announce Type: new Abstract: 3D global relocalization is one of the key capabilities for mobile robots in practical applications. However, in large scale spaces, existing methods of

applicationsarxiv-cs-ro

11 May 2026

RetimeGS: Continuous-Time Reconstruction of 4D Gaussian Splatting

arXiv:2603.13783v2 Announce Type: replace Abstract: Temporal retiming, the ability to reconstruct and render dynamic scenes at arbitrary timestamps, is crucial for applications such as slow-motion pla

7 May 2026

A Scoping Review of Deep Learning Methods for Photoplethysmography Data

arXiv:2401.12783v3 Announce Type: replace-cross Abstract: Background: Photoplethysmography (PPG) is a non-invasive optical sensing technique widely used to capture hemodynamic information, with broad

DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data

arXiv:2605.03430v1 Announce Type: new Abstract: High-dimensional tabular data lacks a natural feature order, limiting the applicability of permutation-sensitive deep learning models. We propose DynaTa

InsTraj: Instructing Diffusion Models with Travel Intentions to Generate Real-world Trajectories

arXiv:2604.04106v2 Announce Type: replace Abstract: The generation of realistic and controllable GPS trajectories is a fundamental task for applications in urban planning, mobility simulation, and pri

Logical Consistency as a Bridge: Improving LLM Hallucination Detection via Label Constraint Modeling between Responses and Self-Judgments

arXiv:2605.03971v1 Announce Type: new Abstract: Large Language Models (LLMs) are prone to factual hallucinations, risking their reliability in real-world applications. Existing hallucination detectors

Adaptive Gait Generation for Multi-Terrain Exoskeletons via Constrained Kernelized Movement Primitives

arXiv:2605.02513v1 Announce Type: new Abstract: Lower limb exoskeletons (LLEs) present the potential to make motor-impaired individuals walk again. Their application in real-world environments is stil

applicationsarxiv-cs-ro

Attribution-Guided Pruning for Insight and Control: Circuit Discovery and Targeted Correction in Small-scale LLMs

arXiv:2506.13727v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely deployed in real-world applications, yet their internal mechanisms remain difficult to interpret and c

Fine-Grained Graph Generation through Latent Mixture Scheduling

arXiv:2605.02780v1 Announce Type: cross Abstract: Structure aware graph generation aims to generate graphs that satisfy given topological properties. It has applications in domains such as drug discov

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

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

ClustViT: Clustering-based Token Merging for Semantic Segmentation

arXiv:2510.01948v2 Announce Type: replace Abstract: Vision Transformers can achieve high accuracy and strong generalization across various contexts, but their practical applicability on real-world rob

4 May 2026

Safety

Exploring LLM biases to manipulate AI search overview

arXiv:2605.00012v1 Announce Type: cross Abstract: Modern large language models (LLMs) are used in many business applications in general, and specifically in web search systems and applications that ge

safetyarxiv-cs-cl

4 May 2026

MMAudio-LABEL: Audio Event Labeling via Audio Generation for Silent Video

arXiv:2605.00495v1 Announce Type: cross Abstract: Recent advances in multimodal generation have enabled high-quality audio generation from silent videos. Practical applications, such as sound producti

4 May 2026

Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models

arXiv:2401.00761v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) like ChatGPT are foundational in various applications due to their extensive knowledge from pre-training and fine

30 Apr 2026

TimeMM: Time-as-Operator Spectral Filtering for Dynamic Multimodal Recommendation

arXiv:2604.26247v1 Announce Type: cross Abstract: Multimodal recommendation improves user modeling by integrating collaborative signals with heterogeneous item content. In real applications, user inte

30 Apr 2026

A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback

arXiv:2604.25025v1 Announce Type: cross Abstract: Preference feedback, in the form of pairwise comparisons rather than scalar scores, has seen increasing use in applications such as human-, laboratory

29 Apr 2026

ASAP: An Azimuth-Priority Strip-Based Search Approach to Planar Microphone Array DOA Estimation in 3D

arXiv:2604.25387v1 Announce Type: cross Abstract: Direction-of-arrival (DOA) estimation is an important task in microphone array processing and many downstream applications. The steered response power

applicationsarxiv-cs-ro

29 Apr 2026

Comparative Insights on Adversarial Machine Learning from Industry and Academia: A User-Study Approach

arXiv:2602.04753v2 Announce Type: replace-cross Abstract: An exponential growth of Machine Learning and its Generative AI applications brings with it significant security challenges, often referred to

LatentStealth: Unnoticeable and Efficient Adversarial Attacks on Expressive Human Pose and Shape Estimation

arXiv:2505.12009v2 Announce Type: replace Abstract: Expressive human pose and shape estimation (EHPS) plays a central role in digital human generation, particularly in live-streaming applications. How

MINT: Multi-Vector Search Index Tuning

arXiv:2504.20018v2 Announce Type: replace-cross Abstract: Vector search plays a crucial role in many real-world applications. In addition to single-vector search, multi-vector search becomes important

Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data

arXiv:2503.05587v3 Announce Type: replace-cross Abstract: Robustness has become a critical attribute for the deployment of RAG systems in real-world applications. Existing research focuses on robustne

LeHome: A Simulation Environment for Deformable Object Manipulation in Household Scenarios

arXiv:2604.22363v1 Announce Type: cross Abstract: Household environments present one of the most common, impactful yet challenging application domains for robotics. Within household scenarios, manipul

27 Apr 2026

ReLeVAnT: Relevance Lexical Vectors for Accurate Legal Text Classification

arXiv:2604.22292v1 Announce Type: cross Abstract: The classification of legal documents from an unstructured data corpus has several crucial applications in downstream tasks. Documents relevant to cou

27 Apr 2026

Discriminative-Generative Synergy for Occlusion Robust 3D Human Mesh Recovery

arXiv:2604.21712v1 Announce Type: new Abstract: 3D human mesh recovery from monocular RGB images aims to estimate anatomically plausible 3D human models for downstream applications, but remains challe

24 Apr 2026

Instance-level Visual Active Tracking with Occlusion-Aware Planning

arXiv:2604.21453v1 Announce Type: new Abstract: Visual Active Tracking (VAT) aims to control cameras to follow a target in 3D space, which is critical for applications like drone navigation and securi

24 Apr 2026

Seeing Further and Wider: Joint Spatio-Temporal Enlargement for Micro-Video Popularity Prediction

arXiv:2604.20311v1 Announce Type: cross Abstract: Micro-video popularity prediction (MVPP) aims to forecast the future popularity of videos on online media, which is essential for applications such as

23 Apr 2026

Towards Energy Impact on AI-Powered 6G IoT Networks: Centralized vs. Decentralized

arXiv:2604.19377v1 Announce Type: new Abstract: The emergence of sixth-generation (6G) technologies has introduced new challenges and opportunities for machine learning (ML) applications in Internet o

22 Apr 2026

An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs

arXiv:2603.04545v2 Announce Type: replace Abstract: Efficient inference for graph neural networks (GNNs) on large knowledge graphs (KGs) is essential for many real-world applications. GNN inference qu

Compositional Steering of Large Language Models with Steering Tokens

arXiv:2601.05062v2 Announce Type: replace Abstract: Deploying LLMs in real-world applications requires controllable output that satisfies multiple desiderata at the same time. While existing work exte

HopRank: Self-Supervised LLM Preference-Tuning on Graphs for Few-Shot Node Classification

arXiv:2604.17271v1 Announce Type: new Abstract: Node classification on text-attributed graphs (TAGs) is a fundamental task with broad applications in citation analysis, social networks, and recommenda

Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure

arXiv:2412.15176v3 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly employed in real-world applications, driving the need to evaluate the trustworthiness of their generat

FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users

arXiv:2502.19312v2 Announce Type: replace-cross Abstract: Effective personalization of LLMs is critical for a broad range of user-interfacing applications such as virtual assistants and content curati

20 Apr 2026

Polyglot: Multilingual Style Preserving Speech-Driven Facial Animation

arXiv:2604.16108v1 Announce Type: new Abstract: Speech-Driven Facial Animation (SDFA) has gained significant attention due to its applications in movies, video games, and virtual reality. However, mos

20 Apr 2026

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning

arXiv:2507.01976v2 Announce Type: replace-cross Abstract: Synthetic network traffic generation has emerged as a promising alternative for various data-driven applications in the networking domain. It

16 Apr 2026

Adaptive Unknown Fault Detection and Few-Shot Continual Learning for Condition Monitoring in Ultrasonic Metal Welding

arXiv:2604.13465v1 Announce Type: new Abstract: Ultrasonic metal welding (UMW) is widely used in industrial applications but is sensitive to tool wear, surface contamination, and material variability,

16 Apr 2026

Radar-Informed 3D Multi-Object Tracking under Adverse Conditions

arXiv:2604.13571v1 Announce Type: new Abstract: The challenge of 3D multi-object tracking (3D MOT) is achieving robustness in real-world applications, for example under adverse conditions and maintain

16 Apr 2026

Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors

arXiv:2510.09536v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in multilingual, real-world applications with user inputs -- naturally introducing typographi

15 Apr 2026

FastGrasp: Learning-based Whole-body Control method for Fast Dexterous Grasping with Mobile Manipulators

arXiv:2604.12879v1 Announce Type: cross Abstract: Fast grasping is critical for mobile robots in logistics, manufacturing, and service applications. Existing methods face fundamental challenges in imp

15 Apr 2026

Uncertainty Quantification on Graph Learning: A Survey

arXiv:2404.14642v4 Announce Type: replace Abstract: Graphical models have demonstrated their exceptional capabilities across numerous applications. However, their performance, confidence, and trustwor

15 Apr 2026

Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptation

arXiv:2604.10950v1 Announce Type: new Abstract: Fully supervised Video Semantic Segmentation (VSS) relies heavily on densely annotated video data, limiting practical applicability. Alternatively, appl

Understanding Generalization in Role-Playing Models via Information Theory

arXiv:2512.17270v2 Announce Type: replace-cross Abstract: Role-playing models (RPMs) are widely used in real-world applications but underperform when deployed in the wild. This degradation can be attr

What Do Vision-Language Models Encode for Personalized Image Aesthetics Assessment?

arXiv:2604.11374v1 Announce Type: cross Abstract: Personalized image aesthetics assessment (PIAA) is an important research problem with practical real-world applications. While methods based on vision

Why Don't You Know? Evaluating the Impact of Uncertainty Sources on Uncertainty Quantification in LLMs

arXiv:2604.10495v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe

WiFlow: A Lightweight WiFi-based Continuous Human Pose Estimation Network with Spatio-Temporal Feature Decoupling

arXiv:2602.08661v2 Announce Type: replace Abstract: Human pose estimation is fundamental to intelligent perception in the Internet of Things (IoT), enabling applications ranging from smart healthcare

Synthesizing real-world distributions from high-dimensional Gaussian Noise with Fully Connected Neural Network

arXiv:2604.09091v1 Announce Type: new Abstract: The use of synthetic data in machine learning applications and research offers many benefits, including performance improvements through data augmentati