Search: “applications”

ECHO: Elastic Speculative Decoding with Sparse Gating for High-Concurrency Scenarios

arXiv:2604.09603v1 Announce Type: cross Abstract: Speculative Decoding promises to accelerate the inference of Large Language Models, yet its efficacy often degrades in production-grade serving. Exist

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Applications

EDUMATH: Generating Standards-aligned Educational Math Word Problems

DGX agent

arXiv:2510.06965v2 Announce Type: replace-cross Abstract: Math word problems (MWPs) are critical K-12 educational tools, and customizing them to students' interests and ability levels can enhance lear

applicationsarxiv-cs-ai

14 Apr 2026

Safety

EE-MCP: Self-Evolving MCP-GUI Agents via Automated Environment Generation and Experience Learning

arXiv:2604.09815v1 Announce Type: new Abstract: Computer-use agents that combine GUI interaction with structured API calls via the Model Context Protocol (MCP) show promise for automating software tas

safetyarxiv-cs-ai

Efficient Transceiver Design for Aerial Image Transmission and Large-scale Scene Reconstruction

arXiv:2604.11098v1 Announce Type: new Abstract: Large-scale three-dimensional (3D) scene reconstruction in low-altitude intelligent networks (LAIN) demands highly efficient wireless image transmission

Explainable Human Activity Recognition: A Unified Review of Concepts and Mechanisms

arXiv:2604.09799v1 Announce Type: cross Abstract: Human activity recognition (HAR) has become a key component of intelligent systems for healthcare monitoring, assistive living, smart environments, an

Exploring Structural Complexity in Normative RAG with Graph-based approaches: A case study on the ETSI Standards

arXiv:2604.09868v1 Announce Type: cross Abstract: Industrial standards and normative documents exhibit intricate hierarchical structures, domain-specific lexicons, and extensive cross-referential depe

Failure Ontology: A Lifelong Learning Framework for Blind Spot Detection and Resilience Design

arXiv:2604.10549v1 Announce Type: new Abstract: Personalized learning systems are almost universally designed around a single objective: help people acquire knowledge and skills more efficiently. We a

FEDBUD: Joint Incentive and Privacy Optimization for Resource-Constrained Federated Learning

arXiv:2604.10499v1 Announce Type: cross Abstract: Federated learning has become a popular paradigm for privacy protection and edge-based machine learning. However, defending against differential attac

FreeScale: Scaling 3D Scenes via Certainty-Aware Free-View Generation

arXiv:2604.10512v1 Announce Type: new Abstract: The development of generalizable Novel View Synthesis (NVS) models is critically limited by the scarcity of large-scale training data featuring diverse

Generating Multiple-Choice Knowledge Questions with Interpretable Difficulty Estimation using Knowledge Graphs and Large Language Models

arXiv:2604.10748v1 Announce Type: cross Abstract: Generating multiple-choice questions (MCQs) with difficulty estimation remains challenging in automated MCQ-generation systems used in adaptive, AI-as

Geoparsing: Diagram Parsing for Plane and Solid Geometry with a Unified Formal Language

arXiv:2604.11600v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress but continue to struggle with geometric reasoning, primarily due to the perce

Research

Gypscie: A Cross-Platform AI Artifact Management System

arXiv:2604.10311v1 Announce Type: new Abstract: Artificial Intelligence (AI) models, encompassing both traditional machine learning (ML) and more advanced approaches such as deep learning and large la

researcharxiv-cs-ai

Head-wise Modality Specialization within MLLMs for Robust Fake News Detection under Missing Modality

arXiv:2604.09711v1 Announce Type: cross Abstract: Multimodal fake news detection (MFND) aims to verify news credibility by jointly exploiting textual and visual evidence. However, real-world news diss

applicationsarxiv-cs-cl

House of Dextra: Cross-embodied Co-design for Dexterous Hands

arXiv:2512.03743v5 Announce Type: replace-cross Abstract: Dexterous manipulation is limited by both control and design, without consensus as to what makes manipulators best for performing dexterous ta

Improving Neutrino Oscillation Measurements through Event Classification

arXiv:2511.11938v2 Announce Type: replace-cross Abstract: Precise neutrino energy reconstruction is essential for next-generation long-baseline oscillation experiments, yet current methods remain limi

Inferring Dynamic Physical Properties from Video Foundation Models

arXiv:2510.02311v2 Announce Type: replace Abstract: We study the task of predicting dynamic physical properties from videos. More specifically, we consider physical properties that require temporal in

Integrating SAINT with Tree-Based Models: A Case Study in Employee Attrition Prediction

arXiv:2604.10337v1 Announce Type: new Abstract: Employee attrition presents a major challenge for organizations, increasing costs and reducing productivity. Predicting attrition accurately enables pro

Learnable Motion-Focused Tokenization for Effective and Efficient Video Unsupervised Domain Adaptation

arXiv:2604.09955v1 Announce Type: new Abstract: Video Unsupervised Domain Adaptation (VUDA) poses a significant challenge in action recognition, requiring the adaptation of a model from a labeled sour

Learning Geometry and Topology via Multi-Chart Flows

arXiv:2505.24665v2 Announce Type: replace Abstract: Real world data often lie on low-dimensional Riemannian manifolds embedded in high-dimensional spaces. This motivates learning degenerate normalizin

Learning Preference-Based Objectives from Clinical Narratives for Sequential Treatment Decision-Making

arXiv:2604.10783v1 Announce Type: new Abstract: Designing reward functions remains a central challenge in reinforcement learning (RL) for healthcare, where outcomes are sparse, delayed, and difficult

Agents

Learning to Assist: Physics-Grounded Human-Human Control via Multi-Agent Reinforcement Learning

arXiv:2603.11346v2 Announce Type: replace Abstract: Humanoid robotics has strong potential to transform daily service and caregiving applications. Although recent advances in general motion tracking w

agentsarxiv-cs-cv

Leveraging Machine Learning Techniques to Investigate Media and Information Literacy Competence in Tackling Disinformation

arXiv:2604.09635v1 Announce Type: cross Abstract: This study develops machine learning models to assess Media and Information Literacy (MIL) skills specifically in the context of disinformation among

LoViF 2026 The First Challenge on Weather Removal in Videos

arXiv:2604.10655v1 Announce Type: cross Abstract: This paper presents a review of the LoViF 2026 Challenge on Weather Removal in Videos. The challenge encourages the development of methods for restori

Masked Training for Robust Arrhythmia Detection from Digitalized Multiple Layout ECG Images

arXiv:2508.09165v3 Announce Type: replace-cross Abstract: Background: Electrocardiograms are indispensable for diagnosing cardiovascular diseases, yet in many settings they exist only as paper printou

MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation

arXiv:2602.05467v2 Announce Type: replace-cross Abstract: Visual Language Navigation (VLN) is one of the fundamental capabilities for embodied intelligence and a critical challenge that urgently needs

applicationsarxiv-cs-cl

ML-Based Real-Time Downlink Performance Prediction in Standalone 5G NR Using Smartphones

arXiv:2604.09632v1 Announce Type: cross Abstract: We propose a machine learning (ML)-based framework for downlink performance prediction in 5G networks using real-time measurements from commercial off

Safety

MobiFlow: Real-World Mobile Agent Benchmarking through Trajectory Fusion

arXiv:2604.09587v1 Announce Type: new Abstract: Mobile agents can autonomously complete user-assigned tasks through GUI interactions. However, existing mainstream evaluation benchmarks, such as Androi

safetyarxiv-cs-ai

Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition

arXiv:2507.20997v4 Announce Type: replace-cross Abstract: In real-world machine learning deployments, models must be continually updated, composed, and when required, selectively undone. However, exis

Non-stationary Diffusion For Probabilistic Time Series Forecasting

arXiv:2505.04278v3 Announce Type: replace-cross Abstract: Due to the dynamics of underlying physics and external influences, the uncertainty of time series often varies over time. However, existing De

NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild

arXiv:2604.11487v1 Announce Type: new Abstract: This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE works

One Scale at a Time: Scale-Autoregressive Modeling for Fluid Flow Distributions

arXiv:2604.11403v1 Announce Type: cross Abstract: Analyzing unsteady fluid flows often requires access to the full distribution of possible temporal states, yet conventional PDE solvers are computatio

Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE

arXiv:2602.17314v2 Announce Type: replace-cross Abstract: Open datasets play a crucial role in three research domains that intersect data science and education: learning analytics, educational data mi

Pacing Opinion Polarization via Graph Reinforcement Learning

arXiv:2602.23390v2 Announce Type: replace-cross Abstract: Opinion polarization moderation has been studied mainly as an analytical optimization problem under the Friedkin Johnson FJ model, where inter

Perceived Importance of Cognitive Skills Among Computing Students in the Era of AI

arXiv:2604.10730v1 Announce Type: cross Abstract: The availability and increasing integration of generative AI tools have transformed computing education. While AI in education presents opportunities,

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs

arXiv:2604.11627v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in cross-modal understanding and generation. However, the ra

Research

PrefPaint: Enhancing Medical Image Inpainting through Expert Human Feedback

arXiv:2506.21834v2 Announce Type: replace Abstract: Inpainting, the process of filling missing or corrupted image parts, has broad applications in medical imaging. However, generating anatomically acc

researcharxiv-cs-cv

ProDiG: Progressive Diffusion-Guided Gaussian Splatting for Aerial to Ground Reconstruction

arXiv:2604.02003v2 Announce Type: replace Abstract: Generating ground-level views and coherent 3D site models from aerial-only imagery is challenging due to extreme viewpoint changes, missing intermed

PRoID: Predicted Rate of Information Delivery in Multi-Robot Exploration and Relaying

arXiv:2604.10433v1 Announce Type: new Abstract: We address Multi-Robot Exploration and Relaying (MRER): a team of robots must explore an unknown environment and deliver acquired information to a fixed

applicationsarxiv-cs-ro

Safety

QShield: Securing Neural Networks Against Adversarial Attacks using Quantum Circuits

arXiv:2604.10933v1 Announce Type: cross Abstract: Deep neural networks remain highly vulnerable to adversarial perturbations, limiting their reliability in security- and safety-critical applications.

safetyarxiv-cs-ai

Quantization Robustness to Input Degradations for Object Detection

arXiv:2508.19600v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is crucial for deploying efficient object detection models, like YOLO, on resource-constrained devices. However, th

Resisting Humanization: Ethical Front-End Design Choices in AI for Sensitive Contexts

arXiv:2603.24853v2 Announce Type: replace Abstract: Ethical debates in AI have primarily focused on back-end issues such as data governance, model training, and algorithmic decision-making. Less atten

RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games

arXiv:2604.11082v1 Announce Type: new Abstract: Visual glitches in video games degrade player experience and perceived quality, yet manual quality assurance cannot scale to the growing test surface of

Retrieving to Recover: Towards Incomplete Audio-Visual Question Answering via Semantic-consistent Purification

arXiv:2604.10695v1 Announce Type: new Abstract: Recent Audio-Visual Question Answering (AVQA) methods have advanced significantly. However, most AVQA methods lack effective mechanisms for handling mis

RF-LEGO: Modularized Signal Processing-Deep Learning Co-Design for RF Sensing via Deep Unrolling

arXiv:2604.10183v1 Announce Type: cross Abstract: Wireless sensing, traditionally relying on signal processing (SP) techniques, has recently shifted toward data-driven deep learning (DL) to achieve pe

Research

RUMLEM: A Dictionary-Based Lemmatizer for Romansh

arXiv:2604.11233v1 Announce Type: new Abstract: Lemmatization -- the task of mapping an inflected word form to its dictionary form -- is a crucial component of many NLP applications. In this paper, we

researcharxiv-cs-cl

SemaCDR: LLM-Powered Transferable Semantics for Cross-Domain Sequential Recommendation

arXiv:2604.09551v1 Announce Type: cross Abstract: Cross-domain recommendation (CDR) addresses the data sparsity and cold-start problems in the target domain by leveraging knowledge from data-rich sour

Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor

arXiv:2604.10554v1 Announce Type: new Abstract: Motion blur arises when rapid scene changes occur during the exposure period, collapsing rich intra-exposure motion into a single RGB frame. Without exp

Model Releases

SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Models

model-releasesarxiv-cs-ai

arXiv:2604.09553v1 Announce Type: cross Abstract: LLM development has aroused great interest in Sequential Recommendation (SR) applications. However, comprehensive evaluation of SR models remains lack