Search: “papers”

Privacy-Preserving Clothing Classification using Vision Transformer for Thermal Comfort Estimation

arXiv:2604.26184v1 Announce Type: new Abstract: A privacy-preserving clothing classification scheme is presented to enable secure occupant-centric control (OCC) systems. Although the utilization of ca

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Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization

DGX agent

arXiv:2604.26073v1 Announce Type: cross Abstract: Industrial chemical plants often operate under strict data confidentiality constraints, making centralized data-driven process modeling difficult. Fed

local-aiarxiv-cs-ai

30 Apr 2026

Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models

arXiv:2604.26508v1 Announce Type: cross Abstract: Deploying Vision-Language Models (VLMs) on edge devices remains challenging due to their substantial computational and memory demands, which exceed th

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch

arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu

R2RGEN: Real-to-Real 3D Data Generation for Spatially Generalized Manipulation

arXiv:2510.08547v2 Announce Type: replace-cross Abstract: Towards the aim of generalized robotic manipulation, spatial generalization is the most fundamental capability that requires the policy to wor

safetyarxiv-cs-cv

Agents

SciHorizon-DataEVA: An Agentic System for AI-Readiness Evaluation of Heterogeneous Scientific Data

arXiv:2604.26645v1 Announce Type: new Abstract: AI-for-Science (AI4Science) is increasingly transforming scientific discovery by embedding machine learning models into prediction, simulation, and hypo

agentsarxiv-cs-ai

SciMDR: Advancing Scientific Multimodal Document Reasoning

arXiv:2603.12249v2 Announce Type: replace-cross Abstract: Constructing scientific multimodal document reasoning datasets for foundation model training involves an inherent trade-off among scale, faith

Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery

arXiv:2502.14912v2 Announce Type: replace Abstract: We present a framework for generating universal semantic embeddings of chemical elements to advance materials inference and discovery. This framewor

SongBench: A Fine-Grained Multi-Aspect Benchmark for Song Quality Assessment

arXiv:2604.25937v1 Announce Type: cross Abstract: Recent advancements in Text-to-Song generation have enabled realistic musical content production, yet existing evaluation benchmarks lack the professi

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness

arXiv:2604.26341v1 Announce Type: new Abstract: Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image

Applications

STAR-Filter: Efficient Convex Free-Space Approximation via Starshaped Set Filtering in Noisy Environments

arXiv:2604.26626v1 Announce Type: new Abstract: Approximating collision-free space is fundamental to robot planning in complex environments. Convex geometric representations, such as polytopes and ell

applicationsarxiv-cs-ro

Agents

Star-Fusion: A Multi-modal Transformer Architecture for Discrete Celestial Orientation via Spherical Topology

arXiv:2604.26582v1 Announce Type: cross Abstract: Reliable celestial attitude determination is a critical requirement for autonomous spacecraft navigation, yet traditional 'Lost-in-Space' (LIS) algori

agentsarxiv-cs-ai

State Beyond Appearance: Diagnosing and Improving State Consistency in Dial-Based Measurement Reading

arXiv:2604.26614v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved impressive progress on general multimodal tasks, yet they remain brittle on dial-based measuremen

Structured and Abstractive Reasoning on Multi-modal Relational Knowledge Images

arXiv:2510.21828v2 Announce Type: replace-cross Abstract: Understanding and reasoning with abstractive information from the visual modality presents significant challenges for current multi-modal larg

SynSur: An end-to-end generative pipeline for synthetic industrial surface defect generation and detection

arXiv:2604.26633v1 Announce Type: cross Abstract: The bottleneck in learning-based industrial defect detection is often limited not by model capacity, but by the scarcity of labeled defect data: defec

researcharxiv-cs-ai

Text Style Transfer with Machine Translation for Graphic Designs

arXiv:2604.26361v1 Announce Type: cross Abstract: Globalization of graphic designs such as those used in marketing materials and magazines is increasingly important for communication to broad audience

safetyarxiv-cs-ai

The Alignment Flywheel: A Governance-Centric Hybrid MAS for Architecture-Agnostic Safety

arXiv:2603.02259v2 Announce Type: replace-cross Abstract: Multi-agent systems provide mature methodologies for role decomposition, coordination, and normative governance, capabilities that remain esse

safetyarxiv-cs-lg

The Bandit's Blind Spot: The Critical Role of User State Representation in Recommender Systems

arXiv:2604.26651v1 Announce Type: cross Abstract: With the increasing availability of online information, recommender systems have become an important tool for many web-based systems. Due to the conti

TildeOpen LLM: Leveraging Curriculum Learning to Achieve Equitable Language Representation

arXiv:2603.08182v2 Announce Type: replace-cross Abstract: Large language models often underperform in many European languages due to the dominance of English and a few high-resource languages in train

U-FaceBP: Uncertainty-aware Bayesian Ensemble Deep Learning for Face Video-based Blood Pressure Estimation

arXiv:2412.10679v3 Announce Type: replace Abstract: Blood pressure (BP) measurement is crucial for daily health assessment. Remote photoplethysmography (rPPG), which extracts pulse waves from face vid

Uncertainty-Aware Information Pursuit for Interpretable and Reliable Medical Image Analysis

arXiv:2506.16742v3 Announce Type: replace Abstract: To be adopted in safety-critical domains like medical image analysis, AI systems must provide human-interpretable decisions. Variational Information

safetyarxiv-cs-cv

Understanding DNNs in Feature Interaction Models: A Dimensional Collapse Perspective

arXiv:2604.26489v1 Announce Type: new Abstract: DNNs have gained widespread adoption in feature interaction recommendation models. However, there has been a longstanding debate on their roles. On one

Unifying Runtime Monitoring Approaches for Safety-Critical Machine Learning: Application to Vision-Based Landing

arXiv:2604.26411v1 Announce Type: new Abstract: Runtime monitoring is essential to ensure the safety of ML applications in safety-critical domains. However, current research is fragmented, with indepe

safetyarxiv-cs-lg

Vertex Features for Neural Global Illumination

arXiv:2508.07852v2 Announce Type: replace-cross Abstract: Recent research on learnable neural representations has been widely adopted in the field of 3D scene reconstruction and neural rendering appli

researcharxiv-cs-ai

A Comparative Study in Surgical AI: Datasets, Foundation Models, and Barriers to Med-AGI

arXiv:2603.27341v2 Announce Type: replace-cross Abstract: Recent Artificial Intelligence (AI) models have matched or exceeded human experts in several benchmarks of biomedical task performance, but su

Tutorials

A New Kind of Network? Review and Reference Implementation of Neural Cellular Automata

arXiv:2604.24990v1 Announce Type: new Abstract: Stephen Wolfram proclaimed in his 2003 seminal work 'A New Kind Of Science' that simple recursive programs in the form of Cellular Automata (CA) are a p

tutorialsarxiv-cs-cv

A Survey on LLM-based Conversational User Simulation

arXiv:2604.24977v1 Announce Type: new Abstract: User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary

Tutorials

Accelerating Regularized Attention Kernel Regression for Spectrum Cartography

arXiv:2604.25138v1 Announce Type: cross Abstract: Spectrum cartography reconstructs spatial radio fields from sparse and heterogeneous wireless measurements, underpinning many sensing and optimization

tutorialsarxiv-cs-lg

Adaptive Meta-Learning Stochastic Gradient Hamiltonian Monte Carlo Simulation for Bayesian Updating of Structural Dynamic Models

arXiv:2604.25710v1 Announce Type: cross Abstract: In the last few decades, Markov chain Monte Carlo (MCMC) methods have been widely applied to Bayesian updating of structural dynamic models in the fie

Agents

Agentic AI for Remote Sensing: Technical Challenges and Research Directions

arXiv:2604.24919v1 Announce Type: new Abstract: Earth Observation (EO) is moving beyond static prediction toward multi-step analytical workflows that require coordinated reasoning over data, tools, an

agentsarxiv-cs-cv

An analysis of sensor selection for fruit picking with suction-based grippers

arXiv:2604.24906v1 Announce Type: cross Abstract: Robotic fruit harvesting often fails to reliably detect whether a fruit has been successfully picked, limiting efficiency and increasing crop damage.

Analyzing LLM Reasoning to Uncover Mental Health Stigma

model-releasesarxiv-cs-cl

arXiv:2604.25053v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly being explored for mental health applications, recent studies reveal that they can exhibit stigma to

ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs

arXiv:2410.24214v3 Announce Type: replace-cross Abstract: Mixed precision quantization has become an important technique for optimizing the execution of deep neural networks (DNNs). Certified robustne

Backtranslation Augmented Direct Preference Optimization for Neural Machine Translation

arXiv:2604.25702v1 Announce Type: new Abstract: Contemporary neural machine translation (NMT) systems are almost exclusively built by training on supervised parallel data. Despite the tremendous progr

Benchmarking Logistic Regression, SVM, and LightGBM Against BiLSTM with Attention for Sentiment Analysis on Indonesian Product Reviews

arXiv:2604.25452v1 Announce Type: new Abstract: Sentiment analysis of product reviews on e-commerce platforms plays a critical role in automatically understanding customer satisfaction and providing a

Benchmarking OCR Pipelines with Adaptive Enhancement for Multi-Domain Retail Bill Digitization

arXiv:2604.25176v1 Announce Type: new Abstract: The digitization of multi-domain retail billing documents remains a challenging task due to variability in scan quality, layout heterogeneity, and domai

Beyond Fidelity: Semantic Similarity Assessment in Low-Level Image Processing

arXiv:2604.25408v1 Announce Type: new Abstract: Low-level image processing has long been evaluated mainly from the perspective of visual fidelity. However, with the rise of deep learning and generativ

BifDet: A 3D Bifurcation Detection Dataset for Airway-Tree Modeling

arXiv:2604.24999v1 Announce Type: new Abstract: Thoracic Computed Tomography (CT) scans offer detailed insights into the intricate branching network of the airway tree, which is essential for understa

Bridging the Indoor-Outdoor Gap: Cross-Technology Ranging for Seamless Robot Navigation

arXiv:2604.25541v1 Announce Type: cross Abstract: Mobile robots that move between outdoor and indoor environments still struggle with consistent positioning. Satellite-based and terrestrial ranging ea

researcharxiv-cs-ro

Bye Bye Perspective API: Lessons for Measurement Infrastructure in NLP, CSS and LLM Evaluation

arXiv:2604.25580v1 Announce Type: new Abstract: The closure of Perspective API at the end of 2026 discards what has functioned as the de facto standard for automated toxicity measurement in NLP, CSS,

Categorical Optimization with Bayesian Anchored Latent Trust Regions for Structural Design under High-Dimensional Uncertainty

arXiv:2604.25241v1 Announce Type: new Abstract: Categorical structural optimization under aleatoric uncertainty is challenging because each design variable must be selected from a finite catalog of ad

CiteRadar: A Citation Intelligence Platform for Researcher Profiling and Geographic Visualization

arXiv:2604.25057v1 Announce Type: new Abstract: Understanding the geographic reach and community structure of one's scholarly citations is increasingly valuable for career development, grant applicati

Dictionary learning for Kernel EDMD

model-releasesarxiv-cs-lg

arXiv:2604.25572v1 Announce Type: cross Abstract: Studying nonlinear dynamical systems through their state space behavior can be challenging, and one possible alternative is to analyze them via their

Tutorials

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity

arXiv:2603.20645v2 Announce Type: replace Abstract: Diffusion models have become a leading framework in generative modeling, yet their theoretical understanding -- especially for high-dimensional data

tutorialsarxiv-cs-lg

DiRe-RAPIDS: Topology-faithful dimensionality reduction at scale

model-releasesarxiv-cs-lg

arXiv:2604.25209v1 Announce Type: new Abstract: Dimensionality reduction methods such as UMAP and t-SNE are central tools for visualising high-dimensional data, but their local-neighborhood objectives

EOS-Bench: A Comprehensive Benchmark for Earth Observation Satellite Scheduling

model-releasesarxiv-cs-ro

arXiv:2604.25782v1 Announce Type: cross Abstract: Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While

EvoTSC: Evolving Feature Learning Models for Time Series Classification via Genetic Programming

model-releasesarxiv-cs-lg

arXiv:2604.25499v1 Announce Type: new Abstract: Time series classification is an important analytical task across diverse domains. However, its practical application is often hindered by the scarcity

Exploring Reasoning Reward Model for Agents

model-releasesarxiv-cs-cl

arXiv:2601.22154v2 Announce Type: replace-cross Abstract: Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However