Search: “applications”

OmniNFT: Modality-wise Omni Diffusion Reinforcement for Joint Audio-Video Generation

arXiv:2605.12480v1 Announce Type: new Abstract: Recent advances in joint audio-video generation have been remarkable, yet real-world applications demand strong per-modality fidelity, cross-modal align

safetyarxiv-cs-cv

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Safety

Prototype Fusion: A Training-Free Multi-Layer Approach to OOD Detection

DGX agent

arXiv:2603.23677v2 Announce Type: replace Abstract: Deep learning models are increasingly deployed in safety-critical applications, where reliable out-of-distribution (OOD) detection is essential to e

safetyarxiv-cs-cv

13 May 2026

Sampling More, Getting Less: Calibration is the Diversity Bottleneck in LLMs

arXiv:2605.11128v1 Announce Type: new Abstract: Diversity is essential for language-model applications ranging from creative generation to scientific discovery, yet modern LLMs often collapse into a n

local-aiarxiv-cs-cl

See the past: Time-Reversed Scene Reconstruction from Thermal Traces Using Visual Language Models

arXiv:2510.05408v2 Announce Type: replace Abstract: Recovering the past from present observations is an intriguing challenge with potential applications in forensics and scene analysis. Thermal imagin

The Midas Touch for Metric Depth

arXiv:2605.11578v1 Announce Type: new Abstract: Recent advances have markedly improved the cross-scene generalization of relative depth estimation, yet its practical applicability remains limited by t

VNDUQE: Information-Theoretic Novelty Detection using Deep Variational Information Bottleneck

arXiv:2605.11551v1 Announce Type: cross Abstract: Detecting out-of-distribution (OOD) samples is critical for safe deployment of neural networks in safety-critical applications. While maximum softmax

safetyarxiv-cs-cv

An Annotation Scheme and Classifier for Personal Facts in Dialogue

model-releasesarxiv-cs-cl

arXiv:2605.10339v1 Announce Type: new Abstract: The advancement of Large Language Models (LLMs) has enabled their application in personalized dialogue systems. We present an extended annotation scheme

Artificial Intelligence in Number Theory: LLMs for Algorithm Generation and Ensemble Methods for Conjecture Verification

arXiv:2504.19451v3 Announce Type: cross Abstract: This paper presents two concrete applications of Artificial Intelligence to algorithmic and analytic number theory. Recent benchmarks of large languag

BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition

model-releasesarxiv-cs-cv

arXiv:2605.08296v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports broad healthcare and behavior science applications. However, data heterogeneity and the

Benchmarking Compositional Generalisation for Machine Learning Interatomic Potentials

arXiv:2605.08988v1 Announce Type: cross Abstract: Machine Learning Interatomic Potentials play a fundamental role in computational chemistry and materials science, enabling applications from molecular

Beyond the Black Box: An Interpretable Machine Learning Framework for Predicting Electronic Structure Microdescriptors and Structure-Performance Relationships in Fe-based Catalytic Systems

arXiv:2605.08994v1 Announce Type: cross Abstract: The current catalyst discovery and development pipeline for energy-intensive applications like methane conversion remains bottlenecked by expensive tr

agentsarxiv-cs-lg

Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation

arXiv:2502.08943v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated significant utility in real-world applications, exhibiting impressive capabilities in natural l

Bridging Sequence and Graph Structure for Epigenetic Age Prediction

arXiv:2605.10541v1 Announce Type: new Abstract: Epigenetic clocks based on DNA methylation have emerged as powerful tools for estimating biological age, with broad applications in aging research, age-

Challenges and opportunities for AI to help deliver fusion energy

arXiv:2603.25777v2 Announce Type: replace-cross Abstract: There is great potential for the application of AI tools in fusion research, and substantial worldwide benefit if fusion power is realised. Ho

Constructive conditional normalizing flows

arXiv:2602.08606v2 Announce Type: replace-cross Abstract: Motivated by applications in conditional sampling, given a probability measure mu and a diffeomorphism phi, we consider the problem of simulta

Tools

Create Vercel Firewall rules with natural language

Vercel introduced a natural language interface for creating Web Application Firewall (WAF) custom rules, allowing users to define firewall policies without writing complex rule syntax. This feature si

toolsvercel-blog

Dependency-Aware Discrete Diffusion for Scene Graph Generation

arXiv:2605.09065v1 Announce Type: new Abstract: Scene graphs (SGs) represent objects and their relationships as structured graphs, enabling applications in image generation, robotics, and 3D understan

safetyarxiv-cs-cv

Tutorials

diffGHOST: Diffusion based Generative Hedged Oblivious Synthetic Trajectories

arXiv:2605.10647v1 Announce Type: new Abstract: Trajectories are nowadays valuable information for a wide range of applications. However they are also inherently sensitive, as they contain highly pers

tutorialsarxiv-cs-ai

Distill, Diffuse, and Semanticize (DDS): Annotation-Free 3D Scene Understanding Based on Multi-Granularity Distillation and Graph-Diffusion-Based Segmentation

arXiv:2605.08293v1 Announce Type: new Abstract: 3D semantic scene understanding has broad applications in digital twins, autonomous driving, smart agriculture, and embodied perception. However, dense

agentsarxiv-cs-cv

Distributional Reinforcement Learning via the Cramer Distance

arXiv:2605.08104v1 Announce Type: new Abstract: This paper explores the application of the Soft Actor-Critic (SAC) algorithm within a Distributional Reinforcement Learning setting and introduces an im

Egocentric Whole-Body Human Mesh Recovery with Prior-Guided Learning

arXiv:2605.08606v1 Announce Type: new Abstract: Egocentric human mesh recovery (HMR) from monocular head-mounted cameras is increasingly important for AR/VR applications, but remains challenging due t

Embedding Dimension Lower Bounds for Universality of Deep Sets and Janossy Pooling

arXiv:2605.08377v1 Announce Type: new Abstract: In many practical applications it is important to build symmetries into neural network architectures. Consider the important case of permutation symmetr

EMO: Pretraining Mixture of Experts for Emergent Modularity

arXiv:2605.06663v2 Announce Type: replace Abstract: Large language models are typically deployed as monolithic systems, requiring the full model even when applications need only a narrow subset of cap

researcharxiv-cs-cl

Explaining Graph Neural Networks for Node Similarity on Graphs

arXiv:2407.07639v2 Announce Type: replace-cross Abstract: Similarity search is a fundamental task for exploiting information in various applications dealing with graph data, such as citation networks

FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection

arXiv:2605.09428v1 Announce Type: new Abstract: Graph-level anomaly detection (GLAD) is crucial for ensuring the reliability of graph-driven applications by identifying abnormal graphs that deviate fr

From Pixels to Concepts: Do Segmentation Models Understand What They Segment?

model-releasesarxiv-cs-cv

arXiv:2605.09591v1 Announce Type: new Abstract: Segmentation is a fundamental vision task underlying numerous downstream applications. Recent promptable segmentation models, such as Segment Anything M

FugSeg: Fast Uncertainty-aware Ground Segmentation for 3D Point Cloud

arXiv:2605.08952v1 Announce Type: new Abstract: In LiDAR-based environment perception systems, ground segmentation is a key preprocessing step supporting various applications such as mapping and navig

Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction

arXiv:2511.17879v4 Announce Type: replace Abstract: Most applications of generative AI involve a sequential interaction in which a person inputs a prompt and waits for a response, and where reaction t

safetyarxiv-cs-lg

Hardware

How Imgix processes 8 billion images daily with G4 VMs powered by NVIDIA Blackwell

The modern web is extremely visual. People are busy and easily-distracted, and smart companies know they have just seconds to attract would-be customers with compelling images, videos, animations, and

hardwaregoogle-cloud-ai

Tutorials

HPGN: Hybrid Priors-Guided Network for Compressed Low-Light Image Enhancement

arXiv:2504.02373v3 Announce Type: replace-cross Abstract: In practical applications, low-light images are often compressed for efficient storage and transmission. Most existing methods disregard compr

tutorialsarxiv-cs-cv

I built ForgePilot: a Codex-style desktop workspace for Ollama with tools, MCP, web research, and document support

ForgePilot is a desktop workspace application designed for Ollama that combines local language model capabilities with development tools, including support for Model Context Protocol (MCP), web resear

local-air-ollama

I shipped an offline SD app for Android. It's slow, your phone will get warm, and it's completely free.

local-air-stablediffusion

I need to check the actual content of this post to provide an accurate summary. A developer released a free, offline Stable Diffusion application for Android that enables local image generation withou

Tutorials

Inductive Entity Representations from Text via Link Prediction

arXiv:2010.03496v4 Announce Type: replace-cross Abstract: Knowledge Graphs (KG) are of vital importance for multiple applications on the web, including information retrieval, recommender systems, and

tutorialsarxiv-cs-ai

LaWM: Least Action World Models for Long-Horizon Physical Consistency from Visual Observations

arXiv:2605.08279v1 Announce Type: cross Abstract: Learning predictive world models from visual observations is a core problem in embodied AI, with applications to model-based reinforcement learning an

Learning the Channel Gain from Anywhere to Anywhere via Cross-environment Transformer Estimators

arXiv:2605.08211v1 Announce Type: cross Abstract: Channel-gain maps provide the channel gain between any two locations in a geographical region. They find numerous applications, from resource allocati

agentsarxiv-cs-lg

LLMSYS-HPOBench: Hyperparameter Optimization Benchmark Suite for Real-World LLM Systems

arXiv:2605.08305v1 Announce Type: cross Abstract: Large Language Model (LLM) systems have been the frontier of AI in many application domains, leading to new challenges and opportunities for hyperpara

Machine Learning-Based Graph Simplification for Symbolic Accelerators

arXiv:2605.08996v1 Announce Type: new Abstract: Graph-based accelerators have been widely adopted in symbolic data processing applications such as genomics, cybersecurity, and artificial intelligence.

Monocular Biomechanical Tracking of Fingers with Inverse Kinematics to Foundation Models

arXiv:2605.09258v1 Announce Type: cross Abstract: Accurate hand and finger tracking from video has significant clinical applications for monitoring activities of daily living and measuring range of mo

Tools

Node.js 26.x now available on Vercel Sandboxes

Vercel has made Node.js 26.x available for use in Vercel Sandboxes, enabling developers to test and run applications with the latest Node.js runtime version. This update allows users to leverage new f

toolsvercel-blog

OCP-GN: A Scalable Second-order Optimizer for Stochastic Optimization

arXiv:2512.24552v2 Announce Type: replace Abstract: This paper proposes a novel second-order optimization algorithm based on the Optimal Control Principle (OCP), applicable to large-scale optimization

PIDNet: Progressive Implicit Decouple Network for Multimodal Action Quality Assessment

arXiv:2605.08945v1 Announce Type: new Abstract: Action quality assessment (AQA) aims to automatically quantify the execution quality of human actions in videos and is valuable for applications such as

PMCTS: Particle Monte Carlo Tree Search for Principled Parallelized Inference Time Scaling

arXiv:2605.08982v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) is a widely used approach for policy improvement through search with increasing popularity for real world applications. D

safetyarxiv-cs-lg

Rethinking Constraint Awareness for Efficient State Embedding of Neural Routing Solver

arXiv:2605.10122v1 Announce Type: new Abstract: Heavy-Encoder-Light-Decoder (HELD) neural routing solvers have emerged as a promising paradigm due to their broad applicability across multiple vehicle

Rethinking Entropy Minimization in Test-Time Adaptation for Autoregressive Models

arXiv:2605.08186v1 Announce Type: cross Abstract: Test-Time Adaptation (TTA) via entropy minimization (EM) has proven effective for classification tasks, yet its application to generative autoregressi

Scaling Mobile Agent Systems: From Capability Density to Collective Intelligence

arXiv:2605.08124v1 Announce Type: cross Abstract: Mobile agent systems are emerging as a key paradigm for enabling intelligent applications on edge devices and in AIoT ecosystems. However, their scala

local-aiarxiv-cs-cl

SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergence

arXiv:2605.10515v1 Announce Type: cross Abstract: The integration of Artificial Intelligence (AI) with Distributed Ledger Technology (DLT) has become a growing research area, yet contributions tend to

agentsarxiv-cs-ai

Spectral Transformer Neural Processes

arXiv:2605.09498v1 Announce Type: cross Abstract: Time series, spatial data, and images are natural applications of Neural Processes. However, when such data exhibit strong periodicity and quasi-perio

Supervised Mixture-of-Experts for Surgical Grasping and Retraction

arXiv:2601.21971v2 Announce Type: replace-cross Abstract: Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due t