Search: “applications”

How does Bayesian Sampling help Membership Inference Attacks?

arXiv:2503.07482v2 Announce Type: replace-cross Abstract: Membership Inference Attacks (MIAs) aim to estimate whether a specific data point was used in the training of a given model. Existing state-of

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Hyperspectral Image Data Reduction for Endmember Extraction

DGX agent

arXiv:2512.10506v3 Announce Type: replace-cross Abstract: Endmember extraction from hyperspectral images aims to identify the spectral signatures of materials present in a scene. Recent studies have s

researcharxiv-cs-lg

26 May 2026

Improving the Completeness and Comparability of Segment Disclosures: A Large Language Model Approach

arXiv:2605.23924v1 Announce Type: new Abstract: Segment-level disclosures are a central component of financial reporting, providing insight into firms' internal organization and the allocation of econ

safetyarxiv-cs-cl

Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System

arXiv:2406.04374v2 Announce Type: replace-cross Abstract: Recommender systems play a crucial role in internet economies by connecting users with relevant products. However, designing effective recomme

IsaacIPC: Coupling High-Fidelity Simulation and Realistic Rendering for Contact-Rich Robotic Systems

arXiv:2605.24339v1 Announce Type: new Abstract: We present IsaacIPC, a robotic simulation framework that couples GPU accelerated incremental potential contact (IPC) with IsaacSim/Lab. IsaacIPC maps si

safetyarxiv-cs-ro

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients

arXiv:2605.24876v1 Announce Type: cross Abstract: We introduce a novel neural operator architecture designed to approximate solutions of linear elliptic partial differential equations with high-contra

LAPLEX: The FFT of Learnable Laplace Kernels

arXiv:2605.24584v1 Announce Type: cross Abstract: Fast linear algebra in deep learning usually comes with a choice: fixed geometry and exact computation, as in the Fourier transform, or adaptive geome

Lean Formalization of Generalization Error Bound by Rademacher Complexity and Dudley's Entropy Integral

arXiv:2503.19605v5 Announce Type: replace-cross Abstract: Understanding and certifying the generalization performance of machine learning algorithms -- i.e. obtaining theoretical estimates of the test

researcharxiv-cs-cl

Learning manifold diffusion semigroups from graph transition matrices

arXiv:2605.25383v1 Announce Type: cross Abstract: We consider graph diffusion processes constructed from finite i.i.d. samples drawn from an unknown manifold embedded in ambient Euclidean space, where

Hardware

Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm

arXiv:2602.05052v3 Announce Type: replace Abstract: We present a unified algorithmic framework for the numerical solution, constrained optimization, and physics-informed learning of PDEs with a variat

hardwarearxiv-cs-lg

Learning Sparse Compositional Functions with Norm-Constrained Neural Networks

model-releasesarxiv-cs-lg

arXiv:2605.25608v1 Announce Type: cross Abstract: The ability of deep neural networks to learn hierarchical features is widely regarded as a key mechanism underlying their success in high-dimensional

Local MAP Sampling for Diffusion Models

arXiv:2510.07343v3 Announce Type: replace-cross Abstract: Diffusion Posterior Sampling (DPS) provides a principled Bayesian approach to inverse problems by sampling from p(x_0 mid y). While posterior

local-aiarxiv-cs-ai

Memory-Induced Tool-Drift in LLM Agents

model-releasesarxiv-cs-lg

arXiv:2605.24941v1 Announce Type: cross Abstract: Modern LLM agents combine long-term memory for personalization with tool-calling interfaces for taking actions in the world -- a combination underpinn

Meta-Engineering Harnesses for AI-Native Software Production: A Contract-Driven Adversarial Verification Architecture with Early Deployment Report

arXiv:2605.25665v1 Announce Type: cross Abstract: AI-native software development is often evaluated at the level of individual models, prompts, or generated artifacts. This framing is insufficient for

MGVQ: Synergizing Multi-dimensional Sensitivity-Aware and Gradient-Hessian Fusion for Vector Quantization

arXiv:2605.24019v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) achieve outstanding performance, yet their huge model size severely hinders deployment on edge devices with limited reso

Micro-Swarm Locomotion Optimization in Dynamic Flow using Multi-Objective Multi-Agent Reinforcement Learning

arXiv:2605.25025v1 Announce Type: new Abstract: Coordinating micro-robotic swarms in physiologically realistic, time-dependent fluid environments remains an unsolved challenge for biomedical and envir

safetyarxiv-cs-ro

MinerU-Popo: Universal Post-Processing Model for Structured Document Parsing

arXiv:2605.24973v1 Announce Type: cross Abstract: VLM-based OCR models have become the de facto choice for document parsing, as they can accurately extract page-level elements (e.g., paragraphs within

researcharxiv-cs-ai

MR-LiDAR: A Multi-Resolution Roadside LiDAR Benchmark for Perception Diagnostics and Deployment Guidance

model-releasesarxiv-cs-ro

arXiv:2605.24777v1 Announce Type: new Abstract: LiDAR model selection is a critical issue in roadside sensing systems, as it directly determines both perception capability and deployment cost. However

Multi-Agent Specification-based Metamorphic Testing of FMU-Based Simulations

arXiv:2605.25101v1 Announce Type: cross Abstract: In many industrial domains, the Functional Mock-up Interface (FMI) is used to exchange simulation models as Functional Mock-up Units (FMUs) across dif

Multi-Alignment Contrastive Learning for Enzyme--Reaction Retrieval

arXiv:2512.08508v2 Announce Type: replace-cross Abstract: Identifying enzymes that catalyze target biochemical reactions is a key step in computational enzyme discovery and biocatalyst design. Recent

safetyarxiv-cs-lg

Multimodal Alignment and Preference Optimization for Zero-Shot Conditional RNA Generation

arXiv:2605.23961v1 Announce Type: cross Abstract: The design of RNA molecules that interact with specific proteins is a critical challenge in experimental and computational biology. Despite recent pro

Neuro-Inspired Inverse Learning for Planning and Control

arXiv:2605.24152v1 Announce Type: new Abstract: We present a neuro-inspired framework for embodied planning and control. Building on three principles that enable fast and highly effective goal-directe

Neuromorphic LiDAR-based Bird's Eye View Object Detection using Energy-efficient Spiking Neural Networks

arXiv:2605.25293v1 Announce Type: cross Abstract: Autonomous driving perception demands accurate and efficient processing of three-dimensional sensor data under strict power constraints. Traditional c

Nystrom Kernel Stein Discrepancy Tests

arXiv:2605.25173v1 Announce Type: cross Abstract: Kernel Stein discrepancy (KSD) is among the most popular goodness-of-fit (GoF) measures on general domains with a large number of successful deploymen

OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization

arXiv:2602.10635v2 Announce Type: replace Abstract: Socially intelligent AI systems must entail reasoning across diverse human behavioral tasks, and generalization to new contexts. However, AI has yet

Optimal Non-Asymptotic Edgeworth Expansions for Multivariate Neural Network Outputs

arXiv:2605.24072v1 Announce Type: cross Abstract: Finite-width fully connected neural networks with Gaussian-initialized weights deviate from their infinite-width Gaussian limit, exhibiting non-vanish

Optimal uncertainty bounds for multivariate kernel regression under bounded noise: A Gaussian process-based dual function

arXiv:2603.16481v2 Announce Type: replace Abstract: Non-conservative uncertainty bounds are essential for making reliable predictions about latent functions from noisy data, and thus, a key enabler fo

Hardware

Optimizing Multidimensional Scaling in Gini Metric Spaces

arXiv:2605.25124v1 Announce Type: new Abstract: The Gini Multidimensional Scaling (Gini MDS) framework extends the Euclidean multidimensional scaling. We introduce a Gini pseudo-distance based on valu

hardwarearxiv-cs-lg

OrpQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization

arXiv:2605.26092v1 Announce Type: cross Abstract: The deployment of Large Language Models (LLMs) and Vision Transformers (ViTs) on edge devices is significantly constrained by memory limitations and t

PairFlow: Closed-Form Source-Target Coupling for Few-Step Generation in Discrete Flow Models

arXiv:2512.20063v3 Announce Type: replace Abstract: We introduce exttt{PairFlow}, a lightweight preprocessing step for training Discrete Flow Models (DFMs) to achieve few-step sampling without requiri

Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection

arXiv:2605.23984v1 Announce Type: cross Abstract: Industrial anomaly detection has attracted significant attention as a fundamental challenge in industrial systems. The rapid advancement of heterogene

Parameter-Efficient VLMs for Gastrointestinal Endoscopy: Medical Image Generation and Clinical Visual Question Answering

arXiv:2605.24792v1 Announce Type: cross Abstract: The major limitations of gastrointestinal (GI) endoscopy AI systems arise from a shortage of annotated data, strict privacy policies, and significant

ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation

arXiv:2605.25029v1 Announce Type: new Abstract: Autonomous parking demands precise low-speed maneuvering within narrow, cluttered, and highly constrained environments, where vehicles must navigate tig

safetyarxiv-cs-ro

Performance Comparison of Classical and Neural Sampling Algorithms for Robotic Navigation

arXiv:2605.25010v1 Announce Type: cross Abstract: Integrating artificial intelligence (AI) into sampling-based motion planning provides new possibilities for improving autonomous navigation efficiency

{Phi}-Noise: Training-Free Temporal Video Conditioning via Phase-Based Noise Manipulation

arXiv:2605.24509v1 Announce Type: cross Abstract: Latent video diffusion models generate videos by progressively transforming Gaussian noise into realistic samples conditioned on text or visual inputs

researcharxiv-cs-ai

PRIMA: Operational Patterns for Resilient Multi-Agent Research with Verifiable Identity and Convergent Feedback

arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov

Quantification of atmospheric carbon dioxide from the Geostationary Operational Environmental Satellite (GOES East)

arXiv:2605.23991v1 Announce Type: cross Abstract: There is a growing urgency to track greenhouse gasses with the resolution, precision and accuracy needed to support independent verification of CO_2 f

local-aiarxiv-cs-lg

Random Neural Network Expressivity for Non-Linear Partial Differential Equations

arXiv:2605.25057v1 Announce Type: cross Abstract: Neural networks with randomly generated hidden weights (RaNNs) have been extensively studied, both as a standalone learning method and as an initializ

Reasoning as an Attack Surface: Adaptive Evolutionary CoT Jailbreaks for LLMs

arXiv:2605.24497v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in reasoning and generation tasks and are increasingly deployed in real-world ap

RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments

model-releasesarxiv-cs-ro

arXiv:2509.17057v3 Announce Type: replace Abstract: We present RoboManipBaselines, an open-source software framework for imitation learning research in robotic manipulation. The framework supports the

Robust inference using density-powered Stein operators

arXiv:2511.03963v2 Announce Type: replace-cross Abstract: We introduce a density-power weighted variant for the Stein operator, called the gamma-Stein operator. This is a novel class of operators deri

Security of OpenClaw Agents: Fundamentals, Attacks, and Countermeasures

arXiv:2605.25435v1 Announce Type: new Abstract: The rapid evolution of large language model (LLM)-driven autonomous agents has given rise to OpenClaw, a new class of open-source agent frameworks that

SimuWoB: Simulating Real-World Mobile Apps for Fast and Faithful GUI Agent Benchmarking

arXiv:2605.25160v1 Announce Type: new Abstract: Mobile GUI agents powered by large language models have progressed rapidly, creating urgent needs for realistic and comprehensive evaluation. Existing b

Tutorials

Small Ensemble-based Data Assimilation: A Machine Learning-Enhanced Data Assimilation Method with Limited Ensemble Size

arXiv:2510.15284v2 Announce Type: replace Abstract: Ensemble-based data assimilation (DA) methods have become increasingly popular due to their inherent ability to address nonlinear dynamic problems.

tutorialsarxiv-cs-lg

Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction

arXiv:2512.05402v2 Announce Type: replace-cross Abstract: Bitcoin mining hardware acquisition requires strategic timing due to volatile markets, rapid technological obsolescence, and protocol-driven r

SoK: A Comprehensive Security Analysis of Jailbreak Resilience in GPT and DeepSeek Models

arXiv:2506.18543v2 Announce Type: replace-cross Abstract: The rapid proliferation of Large Language Models (LLMs) has heightened concerns regarding their exposure to jailbreak attacks, which craft adv

Spatio-temporal, multi-field deep learning of shock propagation in meso-structured media

arXiv:2509.16139v5 Announce Type: replace Abstract: Predicting the extreme hydrodynamic response of porous and architected lattice materials is a fundamental challenge in high energy density physics,

local-aiarxiv-cs-lg

Temporal Score Rescaling for Temperature Sampling in Diffusion and Flow Models

arXiv:2510.01184v2 Announce Type: replace Abstract: We present a mechanism to steer the sampling diversity of denoising diffusion and flow matching models, allowing users to sample from a sharper or b

local-aiarxiv-cs-lg