Search: “papers”

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

researcharxiv-cs-cv

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Safety

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

DGX agent

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

30 Apr 2026

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

Safety

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

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

researcharxiv-cs-cv

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

researcharxiv-cs-cv

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

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

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

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

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

Feasible-First Exploration for Constrained ML Deployment Optimization in Crash-Prone Hierarchical Search Spaces

arXiv:2604.25073v1 Announce Type: new Abstract: Deploying machine learning models under production constraints requires joint optimization over model family, quantization scheme, runtime backend, and

Agents

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling

arXiv:2604.25847v1 Announce Type: cross Abstract: Optimization modeling underpins real-world decision-making in logistics, manufacturing, energy, and public services, but reliably solving such problem

agentsarxiv-cs-lg

Local Ai

From World-Gen to Quest-Line: A Dependency-Driven Prompt Pipeline for Coherent RPG Generation

arXiv:2604.25482v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for narrative generation, but their use in complex, multi-layered role-playing game (RPG) world

local-aiarxiv-cs-cl

GraphPL: Leveraging GNN for Efficient and Robust Modalities Imputation in Patchwork Learning

arXiv:2604.25352v1 Announce Type: new Abstract: Current research on distributed multi-modal learning typically assumes that clients can access complete information across all modalities, which may not

HANDFUL: Sequential Grasp-Conditioned Dexterous Manipulation with Resource Awareness

model-releasesarxiv-cs-ro

arXiv:2604.25126v1 Announce Type: new Abstract: Dexterous robot hands offer rich opportunities for multifunctional manipulation, where a robot must execute multiple skills in sequence while maintainin

Hierarchical Reinforcement Learning for the Dynamic VNE with Alternatives Problem

arXiv:2512.05207v2 Announce Type: replace-cross Abstract: Virtual Network Embedding (VNE) is a key enabler of network slicing, yet most formulations assume that each Virtual Network Request (VNR) has

Image Classification via Random Dilated Convolution with Multi-Branch Feature Extraction and Context Excitation

arXiv:2604.25188v1 Announce Type: new Abstract: Image classification remains a fundamental yet challenging task in computer vision, particularly when fine-grained feature extraction and background noi

Immediate Derivatives Suffice for Online Recurrent Adaptation

arXiv:2603.28750v3 Announce Type: replace Abstract: For three decades online recurrent learning has been assumed to require propagating a Jacobian tensor through the network's dynamics at O(n^4) per s

Investigation into In-Context Learning Capabilities of Transformers

arXiv:2604.25858v1 Announce Type: new Abstract: Transformers have demonstrated a strong ability for in-context learning (ICL), enabling models to solve previously unseen tasks using only example input

Large Language Models Explore by Latent Distilling

arXiv:2604.24927v1 Announce Type: new Abstract: Generating diverse responses is crucial for test-time scaling of large language models (LLMs), yet standard stochastic sampling mostly yields surface-le

Safety

Learning-Based Dynamics Modeling and Robust Control for Tendon-Driven Continuum Robots

arXiv:2604.25691v1 Announce Type: new Abstract: Tendon-Driven Continuum Robots (TDCRs) pose significant modeling and control challenges due to complex nonlinearities, such as frictional hysteresis and

safetyarxiv-cs-ro

Safety

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

safetyarxiv-cs-cl

Lightweight Real-Time Rendering Parameter Optimization via XGBoost-Driven Lookup Tables

arXiv:2604.25178v1 Announce Type: new Abstract: Achieving a desirable balance between rendering quality and real-time performance is a long-standing challenge in modern game and rendering engines, par

Making AI-Assisted Grant Evaluation Auditable without Exposing the Model

arXiv:2604.25200v1 Announce Type: cross Abstract: Public agencies are beginning to consider large language models (LLMs) as decision-support tools for grant evaluation. This creates a practical govern

Measuring the stability and plasticity of recommender systems

arXiv:2508.03941v3 Announce Type: replace-cross Abstract: The typical offline protocol to evaluate recommendation algorithms is to collect a dataset of user-item interactions and then use a part of th

Metric, inertially aligned monocular state estimation via kinetodynamic priors

arXiv:2511.20496v3 Announce Type: replace Abstract: Accurate state estimation for flexible robotic systems poses significant challenges, particularly for platforms with dynamically deforming structure

researcharxiv-cs-ro

MGSM-Pro: A Simple Strategy for Robust Multilingual Mathematical Reasoning Evaluation

arXiv:2601.21225v2 Announce Type: replace Abstract: Large language models have made substantial progress in mathematical reasoning. However, benchmark development for multilingual evaluation has lagge

Minimax Generalized Cross-Entropy

arXiv:2603.19874v3 Announce Type: replace-cross Abstract: Loss functions play a central role in supervised classification. Cross-entropy (CE) is widely used, whereas the mean absolute error (MAE) loss

Applications

Near-Optimal Sample Complexities of Divergence-based S-rectangular Distributionally Robust Reinforcement Learning

arXiv:2505.12202v3 Announce Type: replace Abstract: Distributionally robust reinforcement learning (DR-RL) has recently gained significant attention as a principled approach that addresses discrepanci

applicationsarxiv-cs-lg