Search: “applications”

Skeleton-Based Posture Classification to Promote Safer Walker-Assisted Gait in Older Adults

arXiv:2605.00890v1 Announce Type: new Abstract: Falls among older adults are a significant public health concern, leading to severe injuries, loss of independence, and increased healthcare costs. This

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Applications

Space-Time Forecasting of Dynamic Scenes with Motion-aware Gaussian Grouping

DGX agent

arXiv:2602.21668v2 Announce Type: replace Abstract: Forecasting dynamic scenes remains a fundamental challenge in computer vision, as limited observations make it difficult to capture coherent object-

applicationsarxiv-cs-cv

5 May 2026

SPAT: A Semantic Port-Aware Adaptive-Rate Transmission Protocol for Semantic Communication

arXiv:2605.00897v1 Announce Type: cross Abstract: With the evolution of 6G, semantic communication has emerged as a promising paradigm by prioritizing the delivery of task-relevant meaning over strict

Stochastic Modeling of Human-Machine Authentication Channels under Partial Information Leakage

arXiv:2605.02102v1 Announce Type: cross Abstract: Reliable and secure human-machine communication is fundamental to IoT and cyber-physical ecosystems, where smartphones and wearables commonly serve as

Structural Dilemmas and Developmental Pathways of Legal Argument Mining in the Era of Artificial Intelligence

arXiv:2605.02308v1 Announce Type: new Abstract: Against the backdrop of rapid advances in artificial intelligence, legal argument mining has emerged as an important research area linking legal texts w

Terrain Perception for Agricultural UAVs in Complex Farmland via Rotating mmWave Radar

arXiv:2605.01340v1 Announce Type: new Abstract: Accurate terrain perception is essential for terrain-following flight of agricultural unmanned aerial vehicles (UAVs), yet remains challenging in real-w

applicationsarxiv-cs-ro

The grip of grammar on meaning uncertainty: cross-linguistic evidence, neural correlates, and clinical relevance

arXiv:2605.01537v1 Announce Type: new Abstract: Isolated word meanings are inherently uncertain. This uncertainty reduces when they are combined and anchored in context. We propose that grammar compre

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

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

Weight Clipping for Robust Conformal Inference under Unbounded Covariate Shifts

arXiv:2605.02072v1 Announce Type: new Abstract: Conformal prediction (CP) provides powerful, distribution-free prediction sets, but its guarantees rely on the exchangeability of training and test data

What price to pay? Auto-tuning a building MPC controller for optimal economic cost

arXiv:2501.10859v2 Announce Type: replace-cross Abstract: Demand-side management (DSM) programs introduce complex pricing, requiring advanced control for cost minimization. Model Predictive Control (M

Agents

An End-to-End Decision-Aware Multi-Scale Attention-Based Model for Explainable Autonomous Driving

arXiv:2605.00291v1 Announce Type: new Abstract: The application of computer vision is gradually increasing across various domains. They employ deep learning models with a black-box nature. Without the

agentsarxiv-cs-cv

Are You the A-hole? A Fair, Multi-Perspective Ethical Reasoning Framework

arXiv:2605.00270v1 Announce Type: new Abstract: Standard methods for aggregating natural language judgments, such as majority voting, often fail to produce logically consistent results when applied to

Autoformalizing Memory Specifications with Agents

arXiv:2605.00058v1 Announce Type: cross Abstract: The primary goal of Design Verification (DV) is to ensure that a proposed chip design implementation (either in code, or physical form) exactly matche

Being-H0.7: A Latent World-Action Model from Egocentric Videos

arXiv:2605.00078v1 Announce Type: cross Abstract: Visual-Language-Action models (VLAs) have advanced generalist robot control by mapping multimodal observations and language instructions directly to a

Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots

arXiv:2605.00545v1 Announce Type: new Abstract: Inferring cellular trajectories from destructive snapshots is complicated by the challenges of stochasticity and non-conservative mass dynamics such as

Binomial flows: Denoising and flow matching for discrete ordinal data

arXiv:2605.00360v1 Announce Type: new Abstract: Flow-based generative modeling in continuous spaces exploit Tweedie's formula to express the denoiser (learned in training) as a score function (used in

BWLA: Breaking the Barrier of W1AX Post-Training Quantization for LLMs

arXiv:2605.00422v1 Announce Type: new Abstract: Large language models (LLMs) have driven major progress in NLP, yet their substantial memory and compute demands still hinder practical deployment. Bina

Diffusion Models are Secretly Zero-Shot 3DGS Harmonizers

arXiv:2503.06740v2 Announce Type: replace Abstract: Gaussian Splatting has become a popular technique for various 3D Computer Vision tasks, including novel view synthesis, scene reconstruction, and dy

Evaluating Legal Reasoning Traces with Legal Issue Tree Rubrics

arXiv:2512.01020v2 Announce Type: replace-cross Abstract: Evaluating the quality of LLM-generated reasoning traces in expert domains (e.g., law) is essential for ensuring credibility and explainabilit

FieryGS: In-the-Wild Fire Synthesis with Physics-Integrated Gaussian Splatting

arXiv:2605.00177v1 Announce Type: cross Abstract: We consider the problem of synthesizing photorealistic, physically plausible combustion effects in in-the-wild 3D scenes. Traditional CFD and graphics

GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables

arXiv:2603.08032v2 Announce Type: replace Abstract: Exogenous variables offer valuable supplementary information for predicting future endogenous variables. Forecasting with exogenous variables needs

Geometric analysis of attractor boundaries and storage capacity limits in kernel Hopfield networks

arXiv:2605.00366v1 Announce Type: cross Abstract: High-capacity associative memories based on Kernel Logistic Regression (KLR) exhibit strong storage capabilities, but the dynamical and geometric mech

GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space

arXiv:2605.00498v1 Announce Type: new Abstract: Recent advances in Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made it standard practice to reconstruct 3D scenes from multi-vie

Graph Concept Bottleneck Models

arXiv:2508.14255v2 Announce Type: replace Abstract: Concept Bottleneck Models (CBMs) provide explicit interpretations for deep neural networks through concepts and allow intervention with concepts to

Incomplete Data, Complete Dynamics: A Diffusion Approach

arXiv:2509.20098v2 Announce Type: replace Abstract: Learning physical dynamics from data is a fundamental challenge in machine learning and scientific modeling. Real-world observational data are inher

LambdaRankIC: Directly Optimizing Rank IC for Financial Prediction

arXiv:2605.00501v1 Announce Type: new Abstract: In financial predictions, the performance of machine learning models is often assessed by Rank IC, which is the Spearman rank correlation between the mo

Language Models Struggle to Use Representations Learned In-Context

arXiv:2602.04212v2 Announce Type: replace Abstract: Though large language models (LLMs) have enabled great success across a wide variety of tasks, they still appear to fall short of one of the loftier

LIMSSR: LLM-Driven Sequence-to-Score Reasoning under Training-Time Incomplete Multimodal Observations

arXiv:2605.00434v1 Announce Type: new Abstract: Real-world multimodal learning is often hindered by missing modalities. While Incomplete Multimodal Learning (IML) has gained traction, existing methods

Mutatis Mutandis: Revisiting the Comparator in Discrimination Testing

arXiv:2405.13693v4 Announce Type: replace Abstract: Testing for individual discrimination involves deriving a profile, the comparator, similar to the one making the discrimination claim, the complaina

Network Digital Untwinning: Towards Backward Optimization of Digital Twins

arXiv:2605.00169v1 Announce Type: cross Abstract: Network digital twins (NDTs) are transforming network management by offering precise virtual replicas of physical network systems. However, their reli

One Good Source is All You Need: Near-Optimal Regret for Bandits under Heterogeneous Noise

arXiv:2602.14474v2 Announce Type: replace Abstract: We study K-armed Multiarmed Bandit (MAB) problem with M heterogeneous data sources, each exhibiting unknown and distinct noise variances {sigma_j^2}

Safety

Persona-Grounded Safety Evaluation of AI Companions in Multi-Turn Conversations

arXiv:2605.00227v1 Announce Type: new Abstract: There are growing concerns about the risks posed by AI companion applications designed for emotional engagement. Existing safety evaluations often rely

safetyarxiv-cs-cl

Prediction of Alzheimer's Disease Risk Factors from Retinal Images via Deep Learning: Development and Validation of Biologically Relevant Morphological Associations in the UK Biobank

arXiv:2605.00665v1 Announce Type: new Abstract: The systemic, metabolic, lifestyle factors have established associations with Alzheimer's Disease (AD) through epidemiologic and AD-specific biomarker s

Robust Fusion of Object-Level V2X for Learned 3D Object Detection

arXiv:2605.00595v1 Announce Type: new Abstract: Perception for automated driving is largely based on onboard environmental sensors, such as cameras and radar, which are cost-effective but limited by l

Scaling Federated Linear Contextual Bandits via Sketching

arXiv:2605.00500v1 Announce Type: new Abstract: In federated contextual linear bandits, high data dimensionality incurs prohibitive computation and communication costs: local agents perform O(d^3)-tim

Stereo Multistage Spatial Attention for Real-Time Mobile Manipulation Under Visual Scale Variation and Disturbances

arXiv:2605.00471v1 Announce Type: new Abstract: Robots operating in open, unstructured real-world environments must rely on onboard visual perception while autonomously moving across different locatio

applicationsarxiv-cs-ro

Structure-Aware Chunking for Tabular Data in Retrieval-Augmented Generation

arXiv:2605.00318v1 Announce Type: new Abstract: Tabular documents such as CSV and Excel files are widely used in enterprise data pipelines, yet existing chunking strategies for retrieval-augmented gen

Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue

arXiv:2605.00506v1 Announce Type: new Abstract: We model utterance production as probabilistic cost-sensitive choice over contextual alternatives, using information-theoretic notions of cost. We disti

SynQuE: Estimating Synthetic Dataset Quality Without Annotations

arXiv:2511.03928v5 Announce Type: replace Abstract: We introduce and formalize the Synthetic Dataset Quality Estimation (SynQuE) problem: ranking synthetic datasets by their expected real-world task p

Task-Conditioned Uncertainty Costmaps for Legged Locomotion

arXiv:2605.00261v1 Announce Type: new Abstract: Legged robots maintain dynamic feasibility through multicontact interactions with terrain. Learned foothold prediction can provide feasibility-aware cos

applicationsarxiv-cs-ro

TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning

arXiv:2605.00015v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) advance generalization and data efficiency in time series forecasting by unified large-scale pretraining. But TS

Model Releases

Vesselpose: Vessel Graph Reconstruction from Learned Voxel-wise Direction Vectors in 3D Vascular Images

model-releasesarxiv-cs-cv

arXiv:2605.00538v1 Announce Type: new Abstract: Blood vessel segmentation and -tracing are essential tasks in many medical imaging applications. Although numerous methods exist, the prevailing segment

Weisfeiler Lehman Test on Combinatorial Complexes: Generalized Expressive Power of Topological Neural Networks

arXiv:2605.00725v1 Announce Type: new Abstract: Combinatorial complexes have unified set-based (e.g., graphs, hypergraphs) and part-whole (e.g., simplicial, cellular complexes) structures into a commo

A Pattern Language for Resilient Visual Agents

arXiv:2604.28001v1 Announce Type: new Abstract: Integrating multimodal foundation models into enterprise ecosystems presents a fundamental software architecture challenge. Architects must balance comp

applicationsarxiv-cs-ai

A Unified Framework of Hyperbolic Graph Representation Learning Methods

arXiv:2604.28070v1 Announce Type: new Abstract: Hyperbolic geometry has emerged as an effective latent space for representing complex networks, owing to its ability to capture hierarchical organizatio

AI Inference as Relocatable Electricity Demand: A Latency-Constrained Energy-Geography Framework

arXiv:2604.27855v1 Announce Type: cross Abstract: AI inference is becoming a persistent and geographically distributed source of electricity demand. Unlike many traditional electrical loads, inference

applicationsarxiv-cs-ai

Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI

arXiv:2510.04978v5 Announce Type: replace Abstract: The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical per

applicationsarxiv-cs-ai

Safety

Automatic Causal Fairness Analysis with LLM-Generated Reporting

arXiv:2604.27011v1 Announce Type: cross Abstract: AutoML, intended as the process of automating the application of machine learning to real-world problems, is a key step for AI popularisation. Most Au

safetyarxiv-cs-ai