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arXiv:2605.01096v1 Announce Type: new Abstract: Reinforcement Learning (RL) has the potential to enable robots with fast, nonlinear, and unstable dynamics to reach the limits of their performance. How

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Leveraging Ensemble-Based Semi-Supervised Learning for Illicit Account Detection in Ethereum DeFi Transactions

DGX agent

arXiv:2412.02408v3 Announce Type: replace-cross Abstract: The advent of smart contracts has enabled the rapid rise of Decentralized Finance (DeFi) on the Ethereum blockchain, offering substantial rewa

applicationsarxiv-cs-lg

5 May 2026

LGDWT-GS: Local and Global Discrete Wavelet-Regularized 3D Gaussian Splatting for Sparse-View Scene Reconstruction

arXiv:2601.17185v2 Announce Type: replace Abstract: We propose a new method for few-shot 3D reconstruction that integrates global and local frequency regularization to stabilize geometry and preserve

Low-Latency Embedded Driver Monitoring System with a Multi-Task Neural Network

arXiv:2605.02563v1 Announce Type: new Abstract: Road traffic accidents remain a significant global concern, with the majority attributed to human factors such as driver distraction and fatigue. This s

Machine Learning-Augmented Acceleration of Iterative Ptychographic Reconstruction

arXiv:2605.01122v1 Announce Type: new Abstract: Iterative ptychographic reconstruction algorithms are widely used for coherent diffractive imaging but can exhibit slow convergence under realistic expe

applicationsarxiv-cs-lg

Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners

arXiv:2502.08597v3 Announce Type: replace-cross Abstract: We analyze the performance of heterogeneous learning agents in asset markets with stochastic payoffs. Our main focus is on comparing Bayesian

agentsarxiv-cs-ai

mdok-style at SemEval-2026 Task 10: Finetuning LLMs for Conspiracy Detection

arXiv:2605.02712v1 Announce Type: new Abstract: SemEval-2026 Task 10 is focused on conspiracy detection. Specifically, the goal is to detect whether a Reddit comment expresses a conspiracy belief. Our

researcharxiv-cs-cl

Measuring Differences between Conditional Distributions using Kernel Embeddings

arXiv:2605.02260v1 Announce Type: cross Abstract: Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. W

Methods, Data, and Conceptual Change: Reflections from Two Quantitative Diachronic Case Studies

arXiv:2605.02052v1 Announce Type: new Abstract: This discussion paper reflects on how quantitative approaches to historical linguistics interact with dataset properties. Drawing on two worked examples

researcharxiv-cs-cl

Metric-Normalized Posterior Leakage (mPL): Attacker-Aligned Privacy for Joint Consumption

arXiv:2605.01137v1 Announce Type: new Abstract: Metric differential privacy (mDP) strengthens local differential privacy (LDP) by scaling noise to semantic distance, but many machine learning (ML) sys

local-aiarxiv-cs-lg

Middle-mile logistics through the lens of goal-conditioned reinforcement learning

arXiv:2605.02461v1 Announce Type: cross Abstract: Middle-mile logistics describes the problem of routing parcels through a network of hubs linked by trucks with finite capacity. We rephrase this as a

MOC-3D: Manifold-Order Consistency for Text-to-3D Generation

arXiv:2605.01743v1 Announce Type: new Abstract: With the burgeoning development of fields such as the Metaverse, Virtual Reality (VR), and Digital Twins, text-to-3D generation has emerged as a researc

safetyarxiv-cs-cv

Moira: Language-driven Hierarchical Reinforcement Learning for Pair Trading

arXiv:2605.01954v1 Announce Type: cross Abstract: Many sequential decision-making problems exhibit hierarchical structure, where high-level semantic choices constrain downstream actions and feedback i

applicationsarxiv-cs-cl

MooD: An Efficient VA-Driven Affective Image Editing Framework via Fine-Grained Semantic Control

arXiv:2605.02521v1 Announce Type: new Abstract: Affective image editing (AIE) aims to edit visual content to evoke target emotions. However, existing methods often overlook inference efficiency and pr

Motion-Aware Caching for Efficient Autoregressive Video Generation

arXiv:2605.01725v1 Announce Type: new Abstract: Autoregressive video generation paradigms offer theoretical promise for long video synthesis, yet their practical deployment is hindered by the computat

Multi-Branch Non-Homogeneous Image Dehazing via Concentration Partitioning and Image Fusion

arXiv:2605.00885v1 Announce Type: new Abstract: Existing single image dehazing methods have demonstrated satisfactory performance on homogeneous thin-haze images; however, they often struggle with non

Multi-View Hierarchical Representation Learning of Fetal Hemodynamics for Maternal Hypertension Detection at the Edge

arXiv:2605.00872v1 Announce Type: cross Abstract: Hypertensive disorders of pregnancy remain a leading cause of maternal and fetal morbidity worldwide, yet diagnosis relies on intermittent cuff-based

safetyarxiv-cs-cv

NAPS: Attention-Based Fusion of Heterogeneous Physiological Signals

arXiv:2511.03488v2 Announce Type: replace Abstract: Physiological signals are inherently heterogeneous: they are collected under diverse acquisition setups, differ in the number and type of modalities

applicationsarxiv-cs-lg

Tutorials

Natural Gradient Bayesian Filtering: Geometry-Aware Filter for Dynamical Systems

arXiv:2605.02306v1 Announce Type: new Abstract: Bayesian filtering is a cornerstone of state estimation in complex systems such as aerospace systems, yet exact solutions are available only for linear

tutorialsarxiv-cs-ro

Hardware

Need for Speed: Zero-Shot Depth Completion with Single-Step Diffusion

arXiv:2603.10584v2 Announce Type: replace Abstract: We introduce Marigold-SSD, a single-step, late-fusion depth completion framework that leverages strong diffusion priors while eliminating the costly

hardwarearxiv-cs-cv

Observability Conditions and Filter Design for Visual Pose Estimation via Dual Quaternions

arXiv:2605.02054v1 Announce Type: cross Abstract: This paper presents a dual quaternion framework for 6-DOF visual target tracking that addresses key limitations of perspective-n-point (PnP) solvers:

On the explainability of max-plus neural networks

arXiv:2605.00889v1 Announce Type: new Abstract: We investigate the explanability properties of the recently proposed linear-min-max neural networks. At initialization, they can be interpreted as k-med

Protein-Conditioned Multi-Objective Reinforcement Learning for Full-Length mRNA Design

arXiv:2605.01513v1 Announce Type: new Abstract: Designing therapeutic messenger RNA (mRNA) requires creating full-length transcripts that carefully balance stability, translation efficiency, and immun

safetyarxiv-cs-lg

PuppetAI: A Customizable Platform for Designing Tactile-Rich Affective Robot Interaction

arXiv:2602.04787v2 Announce Type: replace-cross Abstract: We introduce PuppetAI, a modular soft robot interaction platform. This platform offers a scalable cable-driven actuation system and a customiz

applicationsarxiv-cs-ro

Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training

arXiv:2511.07328v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) methods enhance LLM performance by efficiently filtering relevant context for LLMs, reducing hallucinations and

Quantifying and Predicting Disagreement in Graded Human Ratings

arXiv:2605.01168v1 Announce Type: new Abstract: It is increasingly recognized that human annotators do not always agree, and such disagreement is inherent in many annotation tasks. However, not all in

researcharxiv-cs-cl

Rate-optimal Design for Anytime Best Arm Identification

arXiv:2510.23199v3 Announce Type: replace-cross Abstract: We consider the best arm identification problem, where the goal is to identify the arm with the highest mean reward from a set of K arms under

applicationsarxiv-cs-lg

Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank

arXiv:2605.01393v1 Announce Type: new Abstract: Motion forecasting often requires trading interpretability for predictive accuracy. Standard anchor-based architectures rely on opaque latent queries th

Reconstructing conformal field theoretical compositions with Transformers

arXiv:2605.01072v1 Announce Type: cross Abstract: We study the use of transformers to reconstruct the compositions of tensor products of two-dimensional rational conformal field theories (RCFTs) based

Recurrent Graph Neural Networks and Arithmetic Circuits

arXiv:2603.05140v2 Announce Type: replace-cross Abstract: We characterise the computational power of recurrent graph neural networks (GNNs) in terms of arithmetic circuits over the real numbers. Our n

Registration-Free Learnable Multi-View Capture of Faces in Dense Semantic Correspondence

arXiv:2605.01450v1 Announce Type: new Abstract: Recent frameworks like ToFu and TEMPEH provide an automated alternative to classical registration pipelines by predicting 3D meshes in dense semantic co

safetyarxiv-cs-cv

Rethinking Low-Light Image Enhancement: A Log-Domain Intensity--Chromaticity Decoupling Perspective

arXiv:2605.02627v1 Announce Type: new Abstract: Explicit reconstruction constraints derived from the decoupled representation are further imposed to suppress abnormal channel amplification and chromat

Riemannian Generative Decoder

arXiv:2506.19133v3 Announce Type: replace Abstract: Euclidean representations distort data with intrinsic non-Euclidean structure. While Riemannian representation learning offers a solution by embeddi

Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers

arXiv:2605.00869v1 Announce Type: cross Abstract: Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health m

local-aiarxiv-cs-cv

Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation

arXiv:2605.00888v1 Announce Type: new Abstract: Wearable sensor-based human gait analysis holds great promise in healthcare, rehabilitation, clinical diagnosis and monitoring, and sports activities. S

applicationsarxiv-cs-cv

Selective Prediction from Agreement: A Lipschitz-Consistent Version Space Approach

arXiv:2605.02611v1 Announce Type: new Abstract: We consider selective classification with abstention in the fixed-pool (or transductive) setting, where the unlabeled pool is given beforehand and only

Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation

arXiv:2602.13833v2 Announce Type: replace Abstract: Generalizing tool manipulation requires both semantic planning and precise physical control. Modern generalist robot policies, such as Vision-Langua

safetyarxiv-cs-ro

Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation

arXiv:2605.01144v1 Announce Type: new Abstract: Whole-slide images (WSIs) present a fundamental challenge for computational pathology due to their extreme resolution, multi-scale heterogeneity, and th

local-aiarxiv-cs-cv

SimPB++: Simultaneously Detecting 2D and 3D Objects from Multiple Cameras

arXiv:2605.01924v1 Announce Type: new Abstract: Simultaneous perception of 2D objects in perspective view and 3D objects in Bird's Eye View (BEV) is challenging for multi-camera autonomous driving. Ex

agentsarxiv-cs-cv

Sound Source Localization for Spatial Mapping of Surgical Actions in Dynamic Scenes

arXiv:2510.24332v3 Announce Type: replace-cross Abstract: Purpose: Surgical scene understanding is key to advancing computer-aided and intelligent surgical systems. Current approaches predominantly re

agentsarxiv-cs-cv

SparseContrast: Dynamic Sparse Attention for Efficient and Accurate Contrastive Learning in Medical Imaging

arXiv:2605.00887v1 Announce Type: new Abstract: We propose SparseContrast, a new framework that merges dynamic sparse attention with contrastive learning for medical imaging, with a focus on chest X-r

Structured Analytic Coherent Point Drift for Non-Rigid Point Set Registration

arXiv:2605.00934v1 Announce Type: new Abstract: We introduce Analytic-CPD, a structured analytic variant of coherent point drift for non-rigid point set registration. The method retains the CPD poster

SUDP: Secret-Use Delegation Protocol for Agentic Systems

arXiv:2604.24920v2 Announce Type: replace-cross Abstract: Agentic systems increasingly act with user secrets for APIs, messaging platforms, and cloud services. Today's bearer-secret interfaces impleme

agentsarxiv-cs-ai

Super-resolution of airborne laser scanning point clouds for forest inventory

arXiv:2605.02201v1 Announce Type: new Abstract: Airborne Laser Scanning (ALS) can collect point clouds across large areas, enabling large-scale forest inventory. However, ALS point clouds are sparse a

local-aiarxiv-cs-cv

Synergistic Perception and Generative Recomposition: A Multi-Agent Orchestration for Expert-Level Building Inspection

arXiv:2603.20143v2 Announce Type: replace Abstract: Building facade defect inspection is fundamental to structural health monitoring and sustainable urban maintenance, yet it remains a formidable chal

agentsarxiv-cs-cv

Temporally Consistent Object 6D Pose Estimation for Robot Control

arXiv:2605.02708v1 Announce Type: cross Abstract: Single-view RGB object pose estimators have reached a level of precision and efficiency that makes them good candidates for vision-based robot control

The elbow statistic: Multiscale clustering statistical significance

arXiv:2603.03235v2 Announce Type: replace-cross Abstract: Selecting the number of clusters remains a fundamental challenge in unsupervised learning. Existing approaches typically focus on identifying

The Geometric Inductive Bias of Grokking: Bypassing Phase Transitions via Architectural Topology

arXiv:2603.05228v3 Announce Type: replace Abstract: Mechanistic interpretability typically relies on post-hoc analysis of trained networks. We instead adopt an interventional approach: testing hypothe

safetyarxiv-cs-lg