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A B-Spline Function Based 3D Point Cloud Unwrapping Scheme for 3D Fingerprint Recognition and Identification

arXiv:2604.16546v1 Announce Type: new Abstract: Three-dimensional (3D) fingerprint recognition and identification offer several advantages over traditional two-dimensional (2D) recognition systems. Th

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Model Releases

A Benchmark Study of Segmentation Models and Adaptation Strategies for Landslide Detection from Satellite Imagery

DGX agent

arXiv:2604.16663v1 Announce Type: new Abstract: Landslide detection from high resolution satellite imagery is a critical task for disaster response and risk assessment, yet the relative effectiveness

model-releasesarxiv-cs-cv

21 Apr 2026

A Community-Based Approach for Stance Distribution and Argument Organization

arXiv:2604.16852v1 Announce Type: new Abstract: The proliferation of online debate platforms and social media has led to an unprecedented volume of argumentative content on controversial topics from m

A Comparative Evaluation of Geometric Accuracy in NeRF and Gaussian Splatting

arXiv:2604.18205v1 Announce Type: new Abstract: Recent advances in neural rendering have introduced numerous 3D scene representations. Although standard computer vision metrics evaluate the visual qua

A Computational Method for Measuring 'Open Codes' in Qualitative Analysis

arXiv:2411.12142v4 Announce Type: replace Abstract: Qualitative analysis is critical to understanding human datasets in many social science disciplines. A central method in this process is inductive c

A deep learning pipeline for PAM50 subtype classification using histopathology images and multi-objective patch selection

arXiv:2604.01798v2 Announce Type: replace Abstract: Breast cancer is a highly heterogeneous disease with diverse molecular profiles. The PAM50 gene signature is widely recognized as a standard for cla

A Discordance-Aware Multimodal Framework with Multi-Agent Clinical Reasoning

arXiv:2604.16333v1 Announce Type: new Abstract: Knee osteoarthritis frequently exhibits discordance between structural damage observed in imaging and patient-reported symptoms such as pain. This misma

agentsarxiv-cs-lg

A Goal Without a Plan Is Just a Wish: Efficient and Effective Global Planner Training for Long-Horizon Agent Tasks

arXiv:2510.05608v2 Announce Type: replace Abstract: Agents based on large language models (LLMs) struggle with brainless trial-and-error and generating hallucinatory actions due to a lack of global pl

A Hamilton-Jacobi Reachability-Guided Search Framework for Efficient and Safe Indoor Planar Robot Navigation

arXiv:2604.17679v1 Announce Type: new Abstract: Autonomous navigation requires planning to reach a goal safely and efficiently in complex and potentially dynamic environments. Graph search-based algor

safetyarxiv-cs-ro

A High-Accuracy Optical Music Recognition Method Based on Bottleneck Residual Convolutions

arXiv:2604.16446v1 Announce Type: new Abstract: Optical Music Recognition (OMR) aims to convert printed or handwritten music score images into editable symbolic representations. This paper presents an

safetyarxiv-cs-cv

Local Ai

A Lightweight Transformer for Pain Recognition from Brain Activity

arXiv:2604.16491v1 Announce Type: new Abstract: Pain is a multifaceted and widespread phenomenon with substantial clinical and societal burden, making reliable automated assessment a critical objectiv

local-aiarxiv-cs-cv

A Machine Learning Approach to Two-Stage Adaptive Robust Optimization

arXiv:2307.12409v3 Announce Type: replace Abstract: We propose an approach based on machine learning to solve two-stage linear adaptive robust optimization (ARO) problems with binary here-and-now vari

A Mechanism Study of Delayed Loss Spikes in Batch-Normalized Linear Models

arXiv:2604.16809v1 Announce Type: cross Abstract: Delayed loss spikes have been reported in neural-network training, but existing theory mainly explains earlier non-monotone behavior caused by overly

A Model and Estimation of the Bitcoin Transaction Fee

arXiv:2604.17183v1 Announce Type: cross Abstract: Bitcoin transaction fees will become more important as the block subsidy declines, but fee formation is hard to study with blockchain data alone becau

A Multi-Agent Approach for Claim Verification from Tabular Data Documents

arXiv:2604.17225v1 Announce Type: new Abstract: We present a novel approach for claim verification from tabular data documents. Recent LLM-based approaches either employ complex pretraining/fine-tunin

Applications

A multimodal and temporal foundation model for virtual patient representations at healthcare system scale

arXiv:2604.18570v1 Announce Type: cross Abstract: Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clin

applicationsarxiv-cs-cl

A Note on TurboQuant and the Earlier DRIVE/EDEN Line of Work

model-releasesarxiv-cs-lg

arXiv:2604.18555v1 Announce Type: new Abstract: This note clarifies the relationship between the recent TurboQuant work and the earlier DRIVE (NeurIPS 2021) and EDEN (ICML 2022) schemes. DRIVE is a 1-

A novel LSTM music generator based on the fractional time-frequency feature extraction

arXiv:2604.17823v1 Announce Type: cross Abstract: In this paper, we propose a novel approach for generating music based on an artificial intelligence (AI) system. We analyze the features of music and

A Probabilistic Consensus-Driven Approach for Robust Counterfactual Explanations

model-releasesarxiv-cs-lg

arXiv:2604.17494v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) are essential for interpreting black-box models, yet they often become invalid when models are slightly changed. Exis

A proposal for PU classification under Non-SCAR using clustering and logistic model

arXiv:2604.17130v1 Announce Type: cross Abstract: The present study aims to investigate a cluster cleaning algorithm that is both computationally simple and capable of solving the PU classification wh

A Quasi-Experimental Developer Study of Security Training in LLM-Assisted Web Application Development

arXiv:2604.17763v1 Announce Type: cross Abstract: This paper presents a controlled quasi-experimental developer study examining whether a layer-based security training package is associated with impro

safetyarxiv-cs-lg

A Rapid Deployment Pipeline for Autonomous Humanoid Grasping Based on Foundation Models

arXiv:2604.17258v1 Announce Type: new Abstract: Deploying a humanoid robot to manipulate a new object has traditionally required one to two days of effort: data collection, manual annotation, 3D model

agentsarxiv-cs-ro

A Real-Time Bike-Pedestrian Safety System with Wide-Angle Perception and Evaluation Testbed for Urban Intersections

arXiv:2604.17046v1 Announce Type: new Abstract: Collisions between cyclists and pedestrians at urban intersections remain a persistent source of injuries, yet few systems attempt real-time warnings to

safetyarxiv-cs-cv

A Real-World Grasping-in-Clutter Performance Evaluation Benchmark for Robotic Food Waste Sorting

model-releasesarxiv-cs-ro

arXiv:2602.18835v2 Announce Type: replace Abstract: Food waste management is critical for sustainability, yet inorganic contaminants hinder recycling potential. Robotic automation accelerates sorting

A Ridge Too Far: Correcting Over-Shrinkage via Negative Regularization

arXiv:2508.17412v4 Announce Type: replace Abstract: Conventional regularization is designed to control variance, but in small-data regression it can also aggravate underfitting when predictive signal

A Scalable Nystrom-Based Kernel Two-Sample Test with Permutations

arXiv:2502.13570v4 Announce Type: replace-cross Abstract: Two-sample hypothesis testing-determining whether two sets of data are drawn from the same distribution-is a fundamental problem in statistics

A Sensitivity Approach to Causal Inference Under Limited Overlap

arXiv:2511.22003v2 Announce Type: replace-cross Abstract: Limited overlap between treated and control groups is a key challenge in observational analysis. Standard approaches like trimming importance

safetyarxiv-cs-lg

A Sugeno Integral View of Binarized Neural Network Inference

arXiv:2604.17967v1 Announce Type: cross Abstract: In this article, we establish a precise connection between binarized neural networks (BNNs) and Sugeno integrals. The advantage of the Sugeno integral

Tutorials

A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions

arXiv:2604.17312v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a powerful post-training paradigm for enhancing the reasoning capabilities of large language models (LLMs). H

tutorialsarxiv-cs-lg

A Survey of Spatial Memory Representations for Efficient Robot Navigation

arXiv:2604.16482v1 Announce Type: new Abstract: As vision-based robots navigate larger environments, their spatial memory grows without bound, eventually exhausting computational resources, particular

A Survey on the Security of Long-Term Memory in LLM Agents: Toward Mnemonic Sovereignty

arXiv:2604.16548v1 Announce Type: cross Abstract: Research on large language model (LLM) security is shifting from 'will the model leak training data' to a more consequential question: can an agent wi

A Systematic Survey and Benchmark of Deep Learning for Molecular Property Prediction in the Foundation Model Era

model-releasesarxiv-cs-lg

arXiv:2604.16586v1 Announce Type: new Abstract: Molecular property prediction integrates quantum chemistry, cheminformatics, and deep learning to connect molecular structure with physicochemical and b

A Text-To-Text Alignment Algorithm for Better Evaluation of Modern Speech Recognition Systems

arXiv:2509.24478v2 Announce Type: replace Abstract: Modern neural networks have greatly improved performance across speech recognition benchmarks. However, gains are often driven by frequent words wit

safetyarxiv-cs-cl

A Transformer and Prototype-based Interpretable Model for Contextual Sarcasm Detection

model-releasesarxiv-cs-cl

arXiv:2503.11838v2 Announce Type: replace Abstract: Sarcasm detection, with its figurative nature, poses unique challenges for affective systems designed to perform sentiment analysis. While these sys

A Two-Phase Deep Learning Framework for Adaptive Time-Stepping in High-Speed Flow Modeling

arXiv:2506.07969v2 Announce Type: replace Abstract: We consider the problem of modeling high-speed flows using machine learning methods. While most prior studies focus on low-speed fluid flows in whic

A Two-Stage Deep Learning Framework for Segmentation of Ten Gastrointestinal Organs from Coronal MR Enterography

arXiv:2604.17118v1 Announce Type: cross Abstract: Accurate segmentation of gastrointestinal (GI) organs in magnetic resonance enterography (MRE) is critical for diagnosing inflammatory bowel disease (

A Two-Stage Multi-Modal MRI Framework for Lifespan Brain Age Prediction

arXiv:2604.16655v1 Announce Type: cross Abstract: The accurate quantification of brain age from MRI has emerged as an important biomarker of brain health. However, existing approaches are often restri

A Unification of Discrete, Gaussian, and Simplicial Diffusion

arXiv:2512.15923v2 Announce Type: replace Abstract: To model discrete sequences such as DNA, proteins, and language using diffusion, practitioners must choose between three major methods: diffusion in

A Unified Compliance Aggregator Framework for Automated Multi-Tool Security Assessment of Linux Systems

arXiv:2604.17256v1 Announce Type: cross Abstract: Assessing the security posture of modern computing systems typically requires the use of multiple specialized tools. These tools focus on different as

A unified convergence theory for adaptive first-order methods in the nonconvex case, including AdaNorm, full and diagonal AdaGrad, Shampoo and Muo

arXiv:2604.17423v1 Announce Type: new Abstract: A unified framework for first-order optimization algorithms fornonconvex unconstrained optimization is proposed that uses adaptivelypreconditioned gradi

A Universal Avoidance Method for Diverse Multi-branch Generation

arXiv:2604.17323v1 Announce Type: new Abstract: Modern generative models still lack human-level creativity, particularly in multi-branch diversity. Prior approaches to address this problem often incur

Abstain-R1: Calibrated Abstention and Post-Refusal Clarification via Verifiable RL

model-releasesarxiv-cs-cl

arXiv:2604.17073v1 Announce Type: new Abstract: Reinforcement fine-tuning improves the reasoning ability of large language models, but it can also encourage them to answer unanswerable queries by gues

Applications

Active World-Model with 4D-informed Retrieval for Exploration and Awareness

arXiv:2604.16733v1 Announce Type: new Abstract: Physical awareness, especially in a large and dynamic environment, is shaped by sensing decisions that determine observability across space, time, and s

applicationsarxiv-cs-cv

Hardware

AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation

arXiv:2604.18348v1 Announce Type: new Abstract: Video diffusion transformers (DiTs) suffer from prohibitive inference latency due to quadratic attention complexity. Existing sparse attention methods e

hardwarearxiv-cs-cv

AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation

arXiv:2604.16625v1 Announce Type: new Abstract: Recent large language model (LLM) agents have shown promise in using execution feedback for test-time adaptation. However, robust self-improvement remai

Adaptive Forensic Feature Refinement via Intrinsic Importance Perception

arXiv:2604.16879v1 Announce Type: new Abstract: With the rapid development of generative models and multimodal content editing technologies, the key challenge faced by synthetic image detection (SID)

Adaptive Local Frequency Filtering for Fourier-Encoded Implicit Neural Representations

arXiv:2604.02846v2 Announce Type: replace Abstract: Fourier-encoded implicit neural representations (INRs) have shown strong capability in modeling continuous signals from discrete samples. However, c

Adaptive Quantized Planetary Crater Detection System for Autonomous Space Exploration

arXiv:2508.18025v4 Announce Type: replace-cross Abstract: Autonomous planetary exploration demands real-time, high-fidelity environmental perception. Standard deep learning models require massive comp

agentsarxiv-cs-cv