Search: “applications”

ConeGaussian: Anti-Aliased Gaussian Ray-Tracing for Generic Central Cameras

arXiv:2609.13397v1 Announce Type: new Abstract: In rendering, a camera is a sampling operator that maps each finite pixel to a bundle of rays. Different camera models change the geometry of this bundl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Tutorials

Deep Learning-based Intelligent Diagnosis of Congenital Uterine Anomalies in 3D Ultrasound

DGX agent

arXiv:2609.15225v1 Announce Type: new Abstract: Objective: To develop an intelligent framework, termed CUA-Net, for the automated classification of congenital uterine anomalies (CUA) without requiring

tutorialsarxiv-cs-cv

15 Sept 2026

Deformable 2D Gaussian Splatting for Efficient 4K Video Compression

arXiv:2609.14129v1 Announce Type: cross Abstract: Ultra-High-Definition (UHD) video presents significant challenges for efficient storage and real-time decoding. Learning-based methods, such as Neural

DiffuTester: Accelerating Unit Test Generation for Diffusion LLMs via Mining Structural Pattern

model-releasesarxiv-cs-cl

arXiv:2509.24975v4 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) enable parallel generation and are promising for unit test generation (UTG), where efficient and large

Document Topic Alignment Metrics for Evaluating Topic Models of Short-Text Public Health Communications on Social Media

arXiv:2609.14256v1 Announce Type: new Abstract: Topic models are widely used to analyze public health-related social media short texts, yet their evaluation remains dominated by metrics that focus ent

safetyarxiv-cs-cl

Early-Stopping Thresholds for ES-HyperNEAT: A Data-Driven Approach from Fitness Dynamics

arXiv:2609.13533v1 Announce Type: cross Abstract: Most hyperparameter configurations for Evolvable-Substrate HyperNEAT (ES-HyperNEAT) produce networks that stagnate at random-guessing performance, was

Efficient Online Inverse Optimization with O(d) Regret

arXiv:2609.13440v1 Announce Type: new Abstract: We give a deterministic algorithm for online inverse linear optimization with regret O(d), uniform in the horizon and O(d^{2}) time per round. A bound o

Tutorials

EI-DDLGN: Efficient Encrypted Inference with Deep Differentiable Logic Gate Networks under TFHE

arXiv:2609.13636v1 Announce Type: cross Abstract: Privacy-preserving inference via Torus Fully Homomorphic Encryption (TFHE) provides strong protection for sensitive data in outsourced deep learning a

tutorialsarxiv-cs-lg

Enabling Streaming User Transcription in Full-Duplex Speech-to-Speech Models

arXiv:2609.15759v1 Announce Type: new Abstract: Full-duplex speech-to-speech (S2S) models enable natural conversational AI by allowing simultaneous listening and speaking. However, these models typica

agentsarxiv-cs-cl

Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving

arXiv:2512.10159v3 Announce Type: replace-cross Abstract: LLMs have shown strong performance in data-rich domains such as programming, but their reliability in engineering tasks remains limited. Circu

Entropy-Punctured Bloom Filters for Memory-Efficient Machine Learning

arXiv:2609.14187v1 Announce Type: cross Abstract: Memory-efficient feature representations are increasingly important in machine learning settings where storage, transmission cost, bandwidth, or priva

Evaluating Contextual Bias in CNN Image Classification: Evidence from Agricultural Benchmark Datasets

model-releasesarxiv-cs-cv

arXiv:2609.14654v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) are typically evaluated using held-out classification accuracy, an approach that presupposes predictions are based

Exact Recovery by Neighborhood Smoothing in Directed Stochastic Block Models

arXiv:2601.16427v3 Announce Type: replace-cross Abstract: We study exact community recovery in sparse directed stochastic block models using neighborhood smoothing of connection-probability profiles.

Exploring Automated Vulnerability Identification in JavaScript Code Using Large Language Models

arXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach

FFVO: A Feedforward Pose Decoder for Long-Horizon Visual Odometry

model-releasesarxiv-cs-cv

arXiv:2609.13733v1 Announce Type: new Abstract: Stable and reliable 4D spatial understanding is fundamental for autonomous driving systems. While feedforward reconstruction networks can estimate camer

Forty Shades of Blue: Quality-Diversity Alignment via Mode-Conditioned Reinforcement Learning

arXiv:2609.14896v1 Announce Type: cross Abstract: A notable byproduct of LLM alignment training is mode collapse: the progressive loss of output diversity that narrows a model's expressivity at infere

safetyarxiv-cs-ai

From Legal Text to AI-specific Risk Sources: A Systematic Analysis of the EU AI Act's High-Risk Requirements

arXiv:2609.13535v1 Announce Type: new Abstract: The EU AI Act introduces mandatory requirements for high-risk AI systems with the explicit goal of ensuring the development and operation of trustworthy

safetyarxiv-cs-ai

From matrix inversion to constraints: provably tighter confidence regions for importance weights in label shift

arXiv:2609.14802v1 Announce Type: cross Abstract: Importance weights are essential in domain adaptation under label shift, yet their utility is often undermined by the finite sample uncertainty associ

agentsarxiv-cs-lg

From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go

arXiv:2412.05445v3 Announce Type: replace-cross Abstract: Online reviews help people make better decisions. Review platforms usually depend on typed input, where leaving a good review requires signifi

agentsarxiv-cs-ai

GaugeDefect: Detecting Surface Anomalies by Curvature of Feature Transport

arXiv:2609.13282v1 Announce Type: new Abstract: Industrial anomaly localization has advanced rapidly with feature-based, reconstruction-based, and distillation-based methods. Most of these methods sco

Generalized Agent Iteration: One Formal Framework for Iterative Policy Improvement and Recursive Self-Improvement

arXiv:2609.13406v1 Announce Type: new Abstract: When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intellig

safetyarxiv-cs-ai

GNN4PPM: Multi-Target Predictive Process Monitoring with Relational Graph Convolutional Networks

arXiv:2609.14534v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) aims at predicting at runtime and as early as possible the future states of a process execution. Common tasks includ

HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness

arXiv:2609.15195v1 Announce Type: new Abstract: Embodied navigation requires agents to interpret visual observations, accumulate spatial knowledge, and execute actions to follow instructions or locate

agentsarxiv-cs-ro

High-Density Automated Valet Parking with Relocation-Free Sequential Operations

arXiv:2603.23803v2 Announce Type: replace-cross Abstract: In this paper, we present DROP, high-Density Relocation-free sequential OPerations in automated valet parking. DROP addresses the challenges i

researcharxiv-cs-ro

Improving the Last-Iterate Guarantees of Anytime Algorithms for Stochastic Monotone Variational Inequalities

arXiv:2609.15257v1 Announce Type: cross Abstract: We analyze a stochastic algorithm with Halpern anchoring for constrained convex-concave problems and monotone variational inequalities. This algorithm

Integrating Multi-view Multi-light Surface Reconstruction into Cultural Heritage Workflows

arXiv:2609.15833v1 Announce Type: new Abstract: Cultural heritage documentation increasingly relies on image-based 3D surface reconstruction, with photogrammetry software making such workflows accessi

L-Lipschitz Gershgorin ResNet Network

arXiv:2502.21279v2 Announce Type: replace-cross Abstract: Deep residual networks (ResNets) have demonstrated outstanding success in computer vision tasks, attributed to their ability to maintain gradi

Learning Multi-Agent Task Assignment and Navigation in the Factory: from Simulation to Real Robots

arXiv:2609.14567v1 Announce Type: cross Abstract: Reinforcement learning (RL) has shown considerable promise for robotic decision-making, yet deploying multi-agent RL (MARL) on physical multi-robot sy

safetyarxiv-cs-lg

Linearized PINN with pretrained nonlinear layers

model-releasesarxiv-cs-lg

arXiv:2609.14926v1 Announce Type: cross Abstract: We propose a linearized Physics-Informed Neural Network (lPINN), a reduced-order neural basis method for forward and inverse differential equations. I

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

arXiv:2609.13287v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) achieve high decoding efficiency through block-parallel, arbitrary-order generation, making them attractive fo

LLaTSA: Large Language Model-Aligned General-Purpose Transient Stability Analysis

arXiv:2609.14374v1 Announce Type: cross Abstract: Dynamic trajectory prediction has become an important paradigm for data-driven transient stability analysis (TSA), yet most existing predictors remain

MCPAgentBench: A Real-world Task Benchmark for Evaluating LLM Agent MCP Tool Use

arXiv:2512.24565v4 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly serving as autonomous agents, and their utilization of external tools via the Model Context Protocol (

N^2: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion

model-releasesarxiv-cs-lg

arXiv:2506.04166v3 Announce Type: replace Abstract: Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretic

Neural-Network Solutions to Real-Space Charge Density and Generalization

arXiv:2609.14906v1 Announce Type: cross Abstract: The Hohenberg-Kohn theorem establishes that, in principle, the ground state (GS) charge density contains all GS information of a many-electron system,

Neural Operators for Nonlinear Functionals on RKHS

model-releasesarxiv-cs-lg

arXiv:2403.12187v2 Announce Type: replace-cross Abstract: Motivated by the abundance of functional data, such as time series and images, we study the approximation and statistical learning of nonlinea

Online Bayesian Node Classification on Inductive Graphs under Distribution Shift

arXiv:2609.13655v1 Announce Type: new Abstract: On evolving graphs, node classifiers must satisfy two key requirements: inductive generalization to newly arriving nodes under distribution shift and ca

safetyarxiv-cs-lg

Orientation Control of Soft Robots via Adiabatic Spectral Submanifolds

arXiv:2609.14376v1 Announce Type: new Abstract: Soft robots are commonly sought for safety-critical interactions in delicate environments, where accurate position and orientation control is imperative

safetyarxiv-cs-ro

PIVOT: Physics-Grounded Verification for AI-Generated Audio-Video Detection

arXiv:2609.15562v1 Announce Type: cross Abstract: As generative models continue to advance, AI-generated content (AIGC) is becoming increasingly realistic, weakening the artifact cues commonly exploit

Predictive Likelihood Ratios for Language Model Watermark Detection

arXiv:2609.15657v1 Announce Type: cross Abstract: Keyed watermark detection tests dependence between observed tokens and pseudorandom variables reconstructed from a secret key. Building on the pivotal

Proving olympiad geometry theorems on a superconducting quantum processor

arXiv:2609.14533v1 Announce Type: cross Abstract: Automated theorem proving seeks to use computational systems to prove or disprove mathematical and logical statements [1, 2]. It underpins a wide rang

Quenched Ensemble Sampling

arXiv:2609.15894v1 Announce Type: cross Abstract: Some of the sharpest challenges in sampling from the energy functions of physical systems arise at phase transitions, where the density of states chan

SALUTE: Benchmarking and Adapting LLMs for the Defense Domain

model-releasesarxiv-cs-cl

arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and

Sanity Checking Causal Representation Learning on a Simple Real-World System

arXiv:2502.20099v3 Announce Type: replace-cross Abstract: We evaluate methods for causal representation learning (CRL) on a simple, real-world system that satisfies the basic problem setup of CRL. The

Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles

arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why i

safetyarxiv-cs-ro

Self-Evolving Memory for Generative Recommendation

arXiv:2609.15598v1 Announce Type: cross Abstract: Generative recommendation has emerged as a promising end-to-end paradigm for personalized recommendation. However, user preferences continuously evolv

Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never had

arXiv:2609.14121v1 Announce Type: new Abstract: The Semantic Web set out to give information a machine-interpretable form so that software could integrate and reason over it. Its standards became scie

agentsarxiv-cs-ai

Shapley Value Estimation for Multi-Site Data with Blockwise-Missing Features

arXiv:2609.14902v1 Announce Type: cross Abstract: Shapley value (SV)-based methods are the prevailing framework for feature attribution in machine learning, yet existing population-level Shapley estim

safetyarxiv-cs-lg

Solar Intelligence

arXiv:2609.13648v1 Announce Type: new Abstract: Solar energy decision support is fragmented across dashboards that provide data without explanation, research papers are slow to parse, and general-purp

agentsarxiv-cs-ai