Search: “applications”

DVFace: Spatio-Temporal Dual-Prior Diffusion for Video Face Restoration

arXiv:2604.14560v1 Announce Type: new Abstract: Video face restoration aims to enhance degraded face videos into high-quality results with realistic facial details, stable identity, and temporal coher

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Applications

Energy-based Regularization for Learning Residual Dynamics in Neural MPC for Omnidirectional Aerial Robots

DGX agent

arXiv:2604.14678v1 Announce Type: cross Abstract: Data-driven Model Predictive Control (MPC) has lately been the core research subject in the field of control theory. The combination of an optimal con

applicationsarxiv-cs-ro

17 Apr 2026

From Black Box to Glass Box: Cross-Model ASR Disagreement to Prioto Review in Ambient AI Scribe Documentation

arXiv:2604.14152v1 Announce Type: cross Abstract: Ambient AI 'scribe' systems promise to reduce clinical documentation burden, but automatic speech recognition (ASR) errors can remain unnoticed withou

From Tokens to Layers: Redefining Stall-Free Scheduling for MoE Serving with Layered Prefill

arXiv:2510.08055v2 Announce Type: replace Abstract: Large Language Model (LLM) inference in production must meet stringent service-level objectives for both time-to-first-token (TTFT) and time-between

Graph-Based Fraud Detection with Dual-Path Graph Filtering

arXiv:2604.14235v1 Announce Type: new Abstract: Fraud detection on graph data can be viewed as a demanding task that requires distinguishing between different types of nodes. Because graph neural netw

Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions

arXiv:2502.16761v2 Announce Type: replace Abstract: Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stage

Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends

arXiv:2604.14034v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or as

Model Releases

MetaDent: Labeling Clinical Images for Vision-Language Models in Dentistry

model-releasesarxiv-cs-cv

arXiv:2604.14866v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have demonstrated significant potential in medical image analysis, yet their application in intraoral photography remains

Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation

arXiv:2604.15101v1 Announce Type: cross Abstract: Learning-to-Rank (LTR) is a supervised machine learning approach that constructs models specifically designed to order a set of items or documents bas

Model-Based Reinforcement Learning under Random Observation Delays

arXiv:2509.20869v2 Announce Type: replace Abstract: Delays frequently occur in real-world environments, yet standard reinforcement learning (RL) algorithms often assume instantaneous perception of the

On the Use of Evolutionary Optimization for the Dynamic Chance Constrained Open-Pit Mine Scheduling Problem

arXiv:2604.13385v1 Announce Type: cross Abstract: Open-pit mine scheduling is a complex real world optimization problem that involves uncertain economic values and dynamically changing resource capaci

PAGE-4D: Disentangled Pose and Geometry Estimation for VGGT-4D Perception

arXiv:2510.17568v5 Announce Type: replace Abstract: Recent 3D feed-forward models, such as the Visual Geometry Grounded Transformer (VGGT), have shown strong capability in inferring 3D attributes of s

Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization

arXiv:2604.15022v1 Announce Type: cross Abstract: Cost-aware routing dynamically dispatches user queries to models of varying capability to balance performance and inference cost. However, the routing

Shapley Value-Guided Adaptive Ensemble Learning for Explainable Financial Fraud Detection with U.S. Regulatory Compliance Validation

arXiv:2604.14231v1 Announce Type: new Abstract: Financial crime costs U.S. institutions over $32 billion each year. Although AI tools for fraud detection have become more advanced, their use in real-w

Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects

arXiv:2510.07890v3 Announce Type: replace Abstract: Research on cross-dialectal transfer from a standard to a non-standard dialect variety has typically focused on text data. However, dialects are pri

Strategic Response of News Publishers to Generative AI

arXiv:2512.24968v4 Announce Type: replace-cross Abstract: Generative AI can adversely impact news publishers by lowering consumer demand. It can also reduce demand for newsroom employees, and increase

Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators

arXiv:2604.01114v2 Announce Type: replace-cross Abstract: As generative AI systems are integrated into educational settings, students often encounter AI-generated output while working through learning

TurboTalk: Progressive Distillation for One-Step Audio-Driven Talking Avatar Generation

arXiv:2604.14580v1 Announce Type: new Abstract: Existing audio-driven video digital human generation models rely on multi-step denoising, resulting in substantial computational overhead that severely

Which bird does not have wings: Negative-constrained KGQA with Schema-guided Semantic Matching and Self-directed Refinement

arXiv:2604.14749v1 Announce Type: new Abstract: Large language models still struggle with faithfulness and hallucinations despite their remarkable reasoning abilities. In Knowledge Graph Question Answ

Automatically Inferring Teachers' Geometric Content Knowledge: A Skills Based Approach

arXiv:2604.13666v1 Announce Type: cross Abstract: Assessing teachers' geometric content knowledge is essential for geometry instructional quality and student learning, but difficult to scale. The Van

Before the First Token: Scale-Dependent Emergence of Hallucination Signals in Autoregressive Language Models

arXiv:2604.13068v1 Announce Type: new Abstract: When do large language models decide to hallucinate? Despite serious consequences in healthcare, law, and finance, few formal answers exist. Recent work

Blind Bitstream-corrupted Video Recovery via Metadata-guided Diffusion Model

arXiv:2604.13906v1 Announce Type: new Abstract: Bitstream-corrupted video recovery aims to restore realistic content degraded during video storage or transmission. Existing methods typically assume th

Decentralized Rank Scheduling for Energy-Constrained Multi-Task Federated Fine-Tuning in Edge-Assisted IoV Networks

arXiv:2508.09532v2 Announce Type: replace Abstract: Federated fine-tuning has emerged as a promising approach for adapting foundation models (FMs) to diverse downstream tasks in edge environments. In

Diagnostics for Individual-Level Prediction Instability in Machine Learning for Healthcare

arXiv:2603.00192v2 Announce Type: replace Abstract: In healthcare, predictive models increasingly inform patient-level decisions, yet little attention is paid to the variability in individual risk est

Fast and Simple Densest Subgraph with Predictions

arXiv:2505.12600v3 Announce Type: replace-cross Abstract: We study the densest subgraph problem and its NP-hard densest at-most-k subgraph variant through the lens of learning-augmented algorithms. We

From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines

arXiv:2604.13468v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large la

Giving Voice to the Constitution: Low-Resource Text-to-Speech for Quechua and Spanish Using a Bilingual Legal Corpus

arXiv:2604.13288v1 Announce Type: new Abstract: We present a unified pipeline for synthesizing high-quality Quechua and Spanish speech for the Peruvian Constitution using three state-of-the-art text-t

Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction

arXiv:2603.12725v3 Announce Type: replace Abstract: In-context operator learning enables neural networks to infer solution operators from contextual examples without weight updates. While prior work h

Guided Transfer Learning for Discrete Diffusion Models

arXiv:2512.10877v4 Announce Type: replace Abstract: Discrete diffusion models (DMs) have achieved strong performance in language and other discrete domains, offering a compelling alternative to autore

HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System

arXiv:2604.14125v1 Announce Type: new Abstract: While end-to-end Vision-Language-Action (VLA) models offer a promising paradigm for robotic manipulation, fine-tuning them on narrow control data often

Hybrid Attention Model Using Feature Decomposition and Knowledge Distillation for Glucose Forecasting

arXiv:2411.10703v3 Announce Type: replace Abstract: The availability of continuous glucose monitors as over-the-counter commodities have created a unique opportunity to monitor a person's blood glucos

Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes

arXiv:2511.05330v2 Announce Type: replace Abstract: Embedding non-restrictive prior knowledge, such as energy conservation laws, into learning methods is a key motive to construct physically consisten

Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment

arXiv:2604.13462v1 Announce Type: cross Abstract: Effective IT change management is important for businesses that depend on software and services, particularly in highly regulated sectors such as fina

Research

Learning Sewing Patterns via Latent Flow Matching of Implicit Fields

arXiv:2601.17740v2 Announce Type: replace Abstract: Sewing patterns define the structural foundation of garments and are essential for applications such as fashion design, fabrication, and physical si

researcharxiv-cs-cv

Lite Any Stereo: Efficient Zero-Shot Stereo Matching

arXiv:2511.16555v3 Announce Type: replace Abstract: Recent advances in stereo matching have focused on accuracy, often at the cost of significantly increased model size. Traditionally, the community h

Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning

arXiv:2601.02902v2 Announce Type: replace-cross Abstract: Symbolic logical reasoning is a critical yet underexplored capability of large language models (LLMs), providing reliable and verifiable decis

Mathematical Reasoning Enhanced LLM for Formula Derivation: A Case Study on Fiber NLI Modellin

arXiv:2604.13062v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated strong capabilities in code generation and text synthesis, yet their potential for sym

Memory Transfer Learning: How Memories are Transferred Across Domains in Coding Agents

arXiv:2604.14004v1 Announce Type: cross Abstract: Memory-based self-evolution has emerged as a promising paradigm for coding agents. However, existing approaches typically restrict memory utilization

MSGS: Multispectral 3D Gaussian Splatting

arXiv:2604.13340v1 Announce Type: new Abstract: We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radia

Neural architectures for resolving references in program code

arXiv:2604.14073v1 Announce Type: new Abstract: Resolving and rewriting references is fundamental in programming languages. Motivated by a real-world decompilation task, we abstract reference rewritin

Power Transform Revisited: Numerically Stable, and Federated

arXiv:2510.04995v3 Announce Type: replace Abstract: Power transforms are popular parametric methods for making data more Gaussian-like, and are widely used as preprocessing steps in statistical analys

SuperGrasp: Single-View Object Grasping via Superquadric Similarity Matching, Evaluation, and Refinement

arXiv:2603.29254v2 Announce Type: replace Abstract: Robotic grasping from single-view observations remains a critical challenge in manipulation. However, existing methods still struggle to generate re

applicationsarxiv-cs-ro

Vectorizing Projection in Manifold-Constrained Motion Planning for Real-Time Whole-Body Control

arXiv:2604.13323v1 Announce Type: new Abstract: Many robot planning tasks require satisfaction of one or more constraints throughout the entire trajectory. For geometric constraints, manifold-constrai

applicationsarxiv-cs-ro

ZoomSpec: A Physics-Guided Coarse-to-Fine Framework for Wideband Spectrum Sensing

arXiv:2604.13568v1 Announce Type: new Abstract: Wideband spectrum sensing for low-altitude monitoring is critical yet challenging due to heterogeneous protocols,large bandwidths, and non-stationary SN

A Geometric Algebra-informed NeRF Framework for Generalizable Wireless Channel Prediction

arXiv:2604.11983v1 Announce Type: cross Abstract: In this paper, we propose the geometric algebra-informed neural radiance fields (GAI-NeRF), a novel framework for wireless channel prediction that lev

A Two-Stage LLM Framework for Accessible and Verified XAI Explanations

arXiv:2604.12543v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to translate the technical outputs of eXplainable Artificial Intelligence (XAI) methods into accessib

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding

arXiv:2604.12335v1 Announce Type: new Abstract: Training multimodal large language models (MLLMs) for video understanding requires large-scale annotated data spanning diverse tasks such as object coun

ArtifactWorld: Scaling 3D Gaussian Splatting Artifact Restoration via Video Generation Models

arXiv:2604.12251v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) delivers high-fidelity real-time rendering but suffers from geometric and photometric degradations under sparse-view constr