Search: “applications”

Multi-View Speech Representation Learning for Parkinson's Disease Detection Using Context-guided Cross-modal Attention

arXiv:2606.09271v1 Announce Type: cross Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria.

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Applications

Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach

DGX agent

arXiv:2606.07585v1 Announce Type: cross Abstract: This thesis addresses group emotion recognition (GER) in-the-wild with a focus on privacy preservation. Unlike traditional emotion recognition methods

applicationsarxiv-cs-ai

9 Jun 2026

Nonparametric LLM Evaluation from Preference Data

arXiv:2601.21816v2 Announce Type: replace Abstract: Evaluating the performance of large language models (LLMs) from human preference data is crucial for obtaining LLM leaderboards. However, many exist

Safety

Normality Calibration in Semi-supervised Graph Anomaly Detection

arXiv:2510.02014v3 Announce Type: replace Abstract: Graph anomaly detection (GAD) has attracted growing interest for its crucial ability to uncover irregular patterns in broad applications. Semi-super

safetyarxiv-cs-lg

Online Learning for Supervisory Switching Control

arXiv:2603.14762v3 Announce Type: replace-cross Abstract: We study supervisory switching control for partially-observed linear dynamical systems. The objective is to identify and deploy a suitable con

Optical Music Recognition for Real-World Manuscripts with Synthetic Data

arXiv:2606.09479v1 Announce Type: new Abstract: Optical Music Recognition (OMR) has seen major progress in model design, with end-to-end methods now capable of recognising notation at all levels of co

PhysGraph: A Physics-aware 3D Scene Graph for Perception and Reasoning

arXiv:2606.08655v1 Announce Type: cross Abstract: To perform a wide range of daily tasks, robots need to construct a 3D representation that is semantically rich, physically grounded, and structured en

Physics-Aware Sparse Learning and Selective Online Adaptation for Euler-Lagrange Robot Dynamics

arXiv:2606.09640v1 Announce Type: new Abstract: Accurate dynamics models are essential for model-based robotic control, yet nominal Euler--Lagrange models often become inaccurate in the presence of pa

QDSP: An Interpretable Structured Learning Framework for Predicting Death or Cerebral Palsy in Very Low Birth Weight Infants

arXiv:2606.07606v1 Announce Type: new Abstract: Very low birth weight infants (VLBWI) are at high risk of mortality and severe neurodevelopmental impairment, including cerebral palsy, yet reliable dis

Real-Time and Accurate Collision-Free Teleoperation via Differentiable Constraint-Based Trajectory Planning

arXiv:2606.08725v1 Announce Type: new Abstract: In teleoperation, the human operator typically controls only the end-effector pose, which often leads to self-collisions of the manipulator and collisio

Routine laboratory trajectories encode the onset of organ-level complications in cancer

arXiv:2606.08538v1 Announce Type: new Abstract: Routine laboratory panels drawn during cancer treatment constitute longitudinal physiological recordings of organ function, yet their temporal structure

RT-SDGOD: Real-Time Single-Domain Generalized Object Detection

arXiv:2606.09367v1 Announce Type: new Abstract: In real-world deployment under strict real-time constraints, weather and imaging variations induce significant distribution shifts, severely degrading d

Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs

arXiv:2502.18493v2 Announce Type: replace-cross Abstract: A piping and instrumentation diagram (P&ID) is a central reference document in chemical process engineering. Currently, chemical engineers man

Selecting New Measurement Locations to Diversify Traffic-Pattern Coverage: A Real-World Evaluation for Total Traffic Volume Estimation

arXiv:2606.07556v1 Announce Type: cross Abstract: Accurate measurement of traffic volumes and flows is vital for modern intelligent transportation. However, despite recent technological advances in se

Self-Supervised Dynamical System Representations for Physiological Time-Series

arXiv:2512.00239v2 Announce Type: replace Abstract: The effectiveness of self-supervised learning (SSL) for physiological time series depends on the ability of a pretraining objective to preserve info

Simultaneous hyperkinetic movement disorders phenotyping: a cross-cohort pediatric transfer study using routine videos, markerless pose estimation and a tabular foundation model

arXiv:2606.07674v1 Announce Type: new Abstract: Objective: To develop and externally test a video-based framework for simultaneous detection of hyperkinetic MDs phenomenologies: dystonia, tremor, myoc

Strategic Integration of Artificial Intelligence in the C-Suite: The Role of the Chief AI Officer

arXiv:2407.10247v3 Announce Type: replace-cross Abstract: The integration of Artificial Intelligence (AI) into corporate strategy has become critical for organizations seeking to maintain competitive

Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records

arXiv:2606.08903v1 Announce Type: new Abstract: Synthetic healthcare data are widely proposed as privacy-preserving substitutes for real patient data, yet their evaluation remains dominated by statist

TBD-VLA: Temporal Block Diffusion Vision Language Action Model

arXiv:2606.07895v1 Announce Type: new Abstract: Discrete Vision-Language-Action (VLA) models typically formulate action generation as next-token prediction over discretized action spaces, conditioning

Towards Graph Foundation Models for Dynamics in Complex Networked Systems: Lessons from Super-Spreader Identification in Multilayer Networks

arXiv:2606.08306v1 Announce Type: new Abstract: Network dynamics - including spreading, influence maximisation, and epidemic modelling - remain largely confined to the transductive paradigm, where mod

Transfer learning for causal forest

arXiv:2606.07693v1 Announce Type: cross Abstract: Transfer learning addresses the challenge of transfering knowledge from one domain to another. Traditional transfer learning focuses on adapting model

UA-DCM: Uncertainty-aware Causal Decision Making via Effect Bound Decomposition

arXiv:2601.22736v2 Announce Type: replace-cross Abstract: Causal inference from observational data can provide strong evidence for finding the best action in a decision-making scenario without having

UAOR: Uncertainty-aware Observation Reinjection for Vision-Language-Action Models

arXiv:2602.18020v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models leverage pretrained Vision-Language Models (VLMs) as backbones to map images and instructions to actions, demons

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision

arXiv:2606.09670v1 Announce Type: cross Abstract: Recent Anomaly Detection methods achieve perfect detection and segmentation scores on well-established datasets, such as MVTec. However, many of these

Wispy to Voluminous: Prior-free Multi-view Capture of Strand-level Facial Hair

arXiv:2606.08041v1 Announce Type: cross Abstract: Facial hair is a defining trait of personal identity, yet remains a critical bottleneck for digital avatars. Recent volumetric methods achieve photore

X-Palm: Paired Multispectral-to-Smartphone Dataset for Cross-Domain Palmprint Authentication

arXiv:2606.08437v1 Announce Type: cross Abstract: Palmprint modality offers a privacy-preserving biometric solution, yet its deployment is hindered by the domain gap between controlled enrollment and

Zero and Few Shot Load Forecasting with Large Language Models

arXiv:2411.11350v2 Announce Type: replace Abstract: Deep learning models have shown strong performance in load forecasting, but they generally require large amounts of data for model training before b

Zero-Flow Encoders

arXiv:2602.00797v3 Announce Type: replace-cross Abstract: Flow-based methods have achieved significant success in various generative modeling tasks, capturing nuanced details within complex data distr

A Human-Sensitive Controller: Adapting to Human Musculoskeletal Disorder-Related Constraints via Reinforcement Learning

arXiv:2504.10102v2 Announce Type: replace Abstract: Work-Related Musculoskeletal Disorders continue to be a major challenge in industrial environments, leading to reduced workforce participation, incr

A machine-learning-assisted progressive digit-randomness screening framework for detecting non-random patterns in raw numerical research data

arXiv:2606.07128v1 Announce Type: new Abstract: Raw numerical datasets remain less systematically examined in integrity screening than images, plagiarism, or summary-statistic inconsistencies. We deve

A Rolling-Window Framework for Churn Prediction and Behavioral Driver Identification

arXiv:2606.06776v1 Announce Type: new Abstract: Customer churn prediction is a central task in customer analytics, particularly in non-contractual, pay-per-use service environments where disengagement

Adversarial Creation and Detection of AI-Generated Social Bot Content

arXiv:2606.07219v1 Announce Type: new Abstract: The convergence of large language models and social bots allows malicious actors to manipulate the information ecosystem by generating human-like conten

applicationsarxiv-cs-cl

alpha-PFN: Fast Entropy Search via In-Context Learning

arXiv:2606.07134v1 Announce Type: new Abstract: Information-theoretic acquisition functions such as Entropy Search (ES) offer a principled exploration-exploitation framework for Bayesian optimization

Are you sure? A Comprehensive and Comprehensible Survey of Uncertainty Quantification in Symbolic Regression

arXiv:2606.06567v1 Announce Type: new Abstract: Symbolic regression (SR) is a class of methods that systematically explore the space of mathematical functions to discover models that accurately captur

AxisGuide: Grounding Robot Action Coordinate System in RGB Observations for Robust Visuomotor Manipulation

arXiv:2606.06761v1 Announce Type: cross Abstract: Visuomotor manipulation policies trained via large-scale behavior cloning have achieved strong semantic scene understanding, yet often fail to reliabl

CL-CLIP: CLIP-Based Continual Learning Framework with Cost-Volume Category Decoupling for Object Detection

arXiv:2606.06978v1 Announce Type: new Abstract: Continual Object Detection (COD) requires a detector to acquire new categories over time while preserving previously learned ones. This goal is closely

Design Once, Deploy at Scale: Template-Driven ML Development for Large Model Ecosystems

arXiv:2603.24963v3 Announce Type: replace Abstract: Modern computational advertising platforms typically rely on recommendation systems to predict user responses, such as click-through rates, conversi

Research

Enhancing Conformal Prediction via Class Similarity

arXiv:2511.19359v2 Announce Type: replace Abstract: Conformal Prediction (CP) has emerged as a powerful statistical framework for high-stakes classification applications. Instead of predicting a singl

researcharxiv-cs-lg

Exploring Reinforcement Learning for Fluid Transitions Between Clinical Mental Healthcare and Everyday Wellness Support

arXiv:2606.06800v1 Announce Type: cross Abstract: Mental health struggles wax and wane, yet clinical and wellness interventions typically operate separately, causing frequent breakdowns at care transi

Federated Foundation Models over Vehicular Networks

arXiv:2606.06786v1 Announce Type: new Abstract: This paper presents a forward-looking vision for integrating the emerging multi-modal multi-task federated foundation models (M3T FedFMs) into vehicular

Graph Neural Network leveraging Higher-order Class Label Connectivity for Heterophilous Graphs

arXiv:2606.07475v1 Announce Type: cross Abstract: Node classification in graph neural networks (GNNs) has been widely applied in various fields of graph analysis. GNNs achieve high-accuracy node class

LRMIL: Efficient Low-Resolution Multiple Instance Learning via High-Resolution Knowledge Distillation for Whole Slide Image Classification

arXiv:2606.06864v1 Announce Type: new Abstract: Multiple instance learning (MIL) has become a standard paradigm for whole slide image (WSI) analysis in digital pathology, as it enables slide-level pre

LUCID: Learning Unified Control for Image Deflaring and Exposure Mastery in Nighttime Photography

arXiv:2606.06901v1 Announce Type: new Abstract: Photography is the art of painting with light, yet nighttime scenes are shaped by competing degradations: intense flares obscure scene structure, while

MalTree: Tracing Malware Evolution from Embeddings at Scale

arXiv:2606.06570v1 Announce Type: cross Abstract: Malware detection remains largely reactive: machine learning models trained on known samples degrade as threats evolve. Understanding evolutionary rel

Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations

arXiv:2606.06779v1 Announce Type: cross Abstract: In multi-vertical e-commerce platforms like DoorDash, relatively newer product verticals such as grocery and retail present a significant opportunity

Multi-FRuGaL: Multimodal Flexible Redundancy-aware Decomposed Gated Learning for Cancer Diagnosis and Prognosis

arXiv:2606.06867v1 Announce Type: new Abstract: Modern medicine relies on heterogeneous data sources spanning radiology, pathology, text reports, and structured clinical information. However, real-wor

Optimal Control Approach for Non-prehensile Ball Juggling Using a 7-DoF Manipulator

arXiv:2606.06704v1 Announce Type: new Abstract: Non-prehensile object manipulation skills are important for real-world robot interactions, enabling highly dynamic tasks such as balancing a glass on a

Proxy Reconstruction Pre-training for Ramp Flow Prediction at Highway Interchanges

arXiv:2510.03381v3 Announce Type: replace-cross Abstract: Interchanges are crucial nodes for vehicle transfers between highways, yet the lack of real-time ramp detectors creates blind spots in traffic