Search: “applications”

Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors

arXiv:2605.18927v1 Announce Type: cross Abstract: Bayesian latent space models offer a principled approach to network representation, but rely on correct specification of both geometry and link functi

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Applications

Bridge: Retrieval-Augmented Spatiotemporal Modeling for Urban Delivery Demand

DGX agent

arXiv:2605.19172v1 Announce Type: cross Abstract: Forecasting urban delivery demand becomes substantially more challenging when newly added service regions lack historical records. Existing spatiotemp

applicationsarxiv-cs-ai

20 May 2026

CAIT: A Syntactic Parsing Toolkit for Child-Adult InTeractions

arXiv:2605.19718v1 Announce Type: new Abstract: CHILDES is a paramount resource for language acquisition studies -- yet computational tools for analyzing its syntactic structure remain limited. Levera

applicationsarxiv-cs-cl

Closed-Loop Hybrid Digital Twin Platform for Connected and Automated Vehicle Validation

arXiv:2605.19490v1 Announce Type: cross Abstract: Comprehensive and efficient validation of connected and automated vehicles (CAVs) is critical prior to real-world deployment. While simulation-based t

CogOmniControl: Reasoning-Driven Controllable Video Generation via Creative Intent Cognition

arXiv:2605.19995v1 Announce Type: new Abstract: Recent diffusion models achieve strong photorealism and fluency in video generation, yet remain fragile under abstract, sparse or complex conditions, le

Colorful Pinball: Density-Weighted Quantile Regression for Conditional Guarantee of Conformal Prediction

arXiv:2512.24139v5 Announce Type: replace Abstract: Although conformal prediction provides robust marginal coverage guarantees, achieving reliable conditional coverage for specific inputs remains chal

Composition of Memory Experts for Diffusion World Models

arXiv:2605.18813v1 Announce Type: cross Abstract: World models aim to predict plausible futures consistent with past observations, a capability central to planning and decision-making in reinforcement

Conflict-Free Replicated Data Types for Neural Network Model Merging: A Two-Layer Architecture Enabling CRDT-Compliant Model Merging Across 26 Strategies

arXiv:2605.19373v1 Announce Type: cross Abstract: All 26 neural network merge strategies we tested including weight averaging, SLERP, TIES, DARE, Fisher merging, and evolutionary approaches -- fail th

DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models

arXiv:2605.18868v1 Announce Type: cross Abstract: While vision and multimodal foundation models underpin critical tasks from perception to complex reasoning, they remain highly vulnerable to adversari

Data-Efficient Self-Supervised Algorithms for Fine-Grained Birdsong Analysis

arXiv:2511.12158v3 Announce Type: replace Abstract: Research in bioacoustics, neuroscience, and linguistics often uses birdsong as a proxy to acquire knowledge across diverse areas. This requires audi

Deep Neural Sheaf Diffusion

arXiv:2605.19021v1 Announce Type: new Abstract: Deep Graph Neural Networks (GNNs) are essential for capturing complex dependencies in graph-structured data. However, scaling GNNs to depth remains chal

Tutorials

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies

arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application

tutorialsarxiv-cs-lg

Exploiting Non-Negativity in DAG Structure Learning

arXiv:2605.19947v1 Announce Type: new Abstract: This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations generated by a linear structural equation model. DAG

Safety

Feature-Space Smoothing: Certified Robustness of Deep Representations

arXiv:2601.16200v3 Announce Type: replace-cross Abstract: Modern deep learning models exhibit strong capabilities across diverse applications, yet remain vulnerable to malicious inputs that induce err

safetyarxiv-cs-cv

Feed-Forward Gaussian Splatting from Sparse Aerial Views

arXiv:2605.19949v1 Announce Type: new Abstract: Reconstructing large-scale urban scenes from sparse aerial views is a crucial yet challenging task. Due to biased top-down and shallow-oblique camera po

FlyMirage: A Fully Automated Generation Pipeline for Diverse and Scalable UAV Flight Data via Generative World Model

arXiv:2605.19600v1 Announce Type: new Abstract: In the field of Vision-Language Navigation (VLN), aerial datasets remain limited in their ability to combine scale, diversity, and realism, often relyin

applicationsarxiv-cs-ro

Geo-Data-Driven HD Map Generation Workflow with Integrated Reference-Free Constraint-Based Verification

arXiv:2605.18921v1 Announce Type: new Abstract: High-definition (HD) maps are core artifacts for automated driving systems, but their generation commonly relies on sensor-intensive mobile mapping camp

applicationsarxiv-cs-ro

Graph-Driven Cross-Industry Real-Time Monitoring Framework for Anti-Money Laundering Detection in Converged Mobility-Energy Supply Chain Networks

arXiv:2605.18844v1 Announce Type: cross Abstract: With the deep integration of the travel and energy industries, cross-industry supply chain finance has gradually become a high-risk field of hidden mo

Inferring Sensitive Attributes from Knowledge Graph Embeddings: Attack and Defense Strategies

arXiv:2605.19644v1 Announce Type: cross Abstract: Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and support for knowledge enrichment and

LaCoVL-FER: Landmark-Guided Contrastive Learning Network with Vision-Language Enhancement for Facial Expression Recognition

arXiv:2605.19821v1 Announce Type: new Abstract: Facial Expression Recognition (FER) in the wild is still challenging due to uncontrolled variations in pose, occlusion, and illumination. Most existing

LLM-MC-Affect: LLM-Based Monte Carlo Modeling of Affective Trajectories and Latent Ambiguity for Interpersonal Dynamic Insight

arXiv:2601.03645v2 Announce Type: replace Abstract: Emotional coordination is a core property of human interaction that shapes how relational meaning is constructed in real time. While text-based affe

applicationsarxiv-cs-cl

Long-term Power Grid Planning via Answer Set Programming

arXiv:2605.20172v1 Announce Type: cross Abstract: The Power grid is a critical infrastructure underpinning all aspects of modern society and its services. Maintaining its effectiveness requires contin

LP-Eval: Rubric and Dataset for Measuring the Quality of Legal Proposition Generation

arXiv:2605.19815v1 Announce Type: cross Abstract: Legal proposition generation is central to legal reasoning and doctrinal scholarship, yet remain under-examined in Legal NLP. This paper investigates

Minimalist Visual Inertial Odometry

arXiv:2605.19990v1 Announce Type: cross Abstract: Visual-Inertial Odometry(VIO), which is critical to mobile robot navigation, uses cameras with a large number of pixels. Capturing and processing came

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

arXiv:2403.07183v4 Announce Type: replace-cross Abstract: We present an approach for estimating the fraction of text in a large corpus which is likely to be substantially modified or produced by a lar

Multi-Token Residual Prediction

arXiv:2605.18817v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) generate text by iteratively denoising masked token sequences, offering a tradeoff between parallelism and quality comp

Multilayer Correlation Clustering

arXiv:2404.16676v2 Announce Type: replace-cross Abstract: We establish Multilayer Correlation Clustering, a novel generalization of Correlation Clustering to the multilayer setting. In this model, we

Multimodal system for skin cancer detection

arXiv:2601.14822v2 Announce Type: replace-cross Abstract: Melanoma detection is vital for early diagnosis and effective treatment. While deep learning models on dermoscopic images have shown promise,

Open-Set Domain Adaptation Under Background Distribution Shift: Challenges and A Provably Efficient Solution

arXiv:2512.01152v4 Announce Type: replace-cross Abstract: As we deploy machine learning systems in the real world, a core challenge is to maintain a model that is performant even as the data shifts. S

Research

OpenComputer: Verifiable Software Worlds for Computer-Use Agents

arXiv:2605.19769v1 Announce Type: new Abstract: We present OpenComputer, a verifier-grounded framework for constructing verifiable software worlds for computer-use agents. OpenComputer integrates four

researcharxiv-cs-ai

Performance Monitoring of Proton Exchange Membrane Water Electrolyzer by Transformers-Based Machine Learning Model

arXiv:2605.19107v1 Announce Type: new Abstract: Green hydrogen plays an essential role in decarbonization, with capacity projected to scale to 560 GW by 2030 (vs. 1.39 GW in 2023) in net-zero settings

Prognostic Value of Lung Ultrasound Biomarkers for Readmission Risk in Congestive Heart Failure: A Pilot Data-Driven Analysis

arXiv:2605.18878v1 Announce Type: cross Abstract: Hospital readmission within 30 days of discharge is a leading driver of morbidity, mortality, and avoidable healthcare expenditure in congestive heart

Quantized Machine Learning Models for Medical Imaging in Low-Resource Healthcare Settings

arXiv:2605.19207v1 Announce Type: cross Abstract: Deep learning models have shown strong performance in medical image analysis, but deploying them in low-resource clinical environments remains difficu

Reducing Diffusion Model Memorization with Higher Order Langevin Dynamics

arXiv:2605.19170v1 Announce Type: cross Abstract: Diffusion/score-based models have emerged as powerful generative models, capable of generating high-quality samples that mimic the training data distr

Scalable, Energy-Efficient Optical-Neural Architecture for Multiplexed Deepfake Video Detection

arXiv:2605.19360v1 Announce Type: new Abstract: The rapid proliferation of AI-generated visual media has created an urgent need for efficient, trustworthy deepfake detection systems. However, existing

Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence

arXiv:2505.23747v2 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have significantly enhanced performance on 2D visual tasks. However, improving

ST-TGExplainer: Disentangling Stability and Transition Patterns for Temporal GNN Interpretability

arXiv:2605.19822v1 Announce Type: cross Abstract: Temporal graph neural networks (TGNNs) have gained significant traction for solving real-world temporal graph tasks. However, their interpretability r

Stability and Discretization Error of State Space Model Neural Operators

arXiv:2605.18905v1 Announce Type: cross Abstract: Neural operators have emerged as a powerful, discretization-invariant framework for solving partial differential equations (PDEs). Although establishe

Taming Real-World Space-Time Video Super-Resolution with One-Step Diffusion

arXiv:2601.20308v2 Announce Type: replace Abstract: Diffusion models have demonstrated exceptional success in video super-resolution (VSR), exhibiting powerful capabilities for generating fine-grained

TERGAD: Structure-Aware Text-Enhanced Representations for Graph Anomaly Detection

arXiv:2605.19738v1 Announce Type: cross Abstract: Graph Anomaly Detection (GAD) aims to identify atypical graph entities, such as nodes, edges, or substructures, that deviate significantly from the ma

Throwing Vines at the Wall: Structure Learning via Random Search

arXiv:2510.20035v3 Announce Type: replace-cross Abstract: Vine copulas offer flexible multivariate dependence modeling and have become widely used in machine learning. Yet, structure learning remains

Variational Diffusion Channel Decoder

arXiv:2605.18902v1 Announce Type: cross Abstract: Neural channel decoder, as a data-driven channel decoding strategy, has shown very promising improvement on error-correcting capability over the class

VCR: Learning Valid Contextual Representation for Incomplete Wearable Signals

arXiv:2605.18837v1 Announce Type: cross Abstract: Wearable devices enable continuous health monitoring from multimodal signals, but real-world deployment is hindered by limited labeled data and pervas

Research

Warm-starting active-set solvers using graph neural networks

arXiv:2511.13174v2 Announce Type: replace Abstract: Quadratic programming (QP) solvers are widely used in real-time control and optimization, but their computational cost often limits applicability in

researcharxiv-cs-lg

Agents

When Web Apps Heal Themselves: A MAPE-K Based Approach to Fault Tolerance and Adaptive Recovery

arXiv:2605.19261v1 Announce Type: cross Abstract: Ensuring the reliability and resilience of modern web applications remains a critical challenge due to increasing system complexity and dynamic runtim

agentsarxiv-cs-ai

A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification

arXiv:2605.17021v1 Announce Type: new Abstract: Multi-view learning has been widely applied for sleep stage classification using multi-modal data. However, existing methods typically assume that diffe

19 May 2026

A Global-Local Graph Attention Network for Traffic Forecasting

arXiv:2605.16726v1 Announce Type: new Abstract: Traffic forecasting is a significant part of intelligent transportation systems. One of the critical challenges of traffic forecasting is to find spatio

19 May 2026

A Machine Learning Framework for EEG-Based Prediction of Treatment Efficacy in Chronic Neck Pain

arXiv:2605.16326v1 Announce Type: cross Abstract: Chronic neck pain is a leading cause of disability worldwide, and current treatment selection remains largely trial and error. We present a machine le