Search: “applications”

Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

arXiv:2608.13457v1 Announce Type: new Abstract: Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative model

researcharxiv-cs-lg

14 Aug 2026

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Safety

BEST-KAG: Enhancing Question Answering of Building Engineering Standards with Multimodal Knowledge Graph Modeling and Large Language Model

DGX agent

arXiv:2608.11244v1 Announce Type: new Abstract: Construction standards are critical for building safety and sustainability. Existing standard application workflows rely on keyword-based document retri

safetyarxiv-cs-ai

13 Aug 2026

COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images

arXiv:2608.11422v1 Announce Type: new Abstract: Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imagi

CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D

arXiv:2509.24528v4 Announce Type: replace-cross Abstract: Object retrieval from a scene has become a new trend of research due to its numerous applications. Recent approaches achieve zero-shot, open-v

Defending against Model Extraction for GNNs with Model Reprogramming

arXiv:2608.11495v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) serve as the backbone for high-stakes applications in Machine-Learning-as-a-Service (MLaaS). Still, their black-box deploym

safetyarxiv-cs-lg

Earth observation embeddings are effective sub-grid descriptors for probabilistic weather downscaling

arXiv:2608.12271v1 Announce Type: new Abstract: Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at ar

researcharxiv-cs-lg

Ethics Practices in AI Development: An Empirical Study Across Roles and Regions

arXiv:2508.09219v3 Announce Type: replace-cross Abstract: Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks po

researcharxiv-cs-ai

Forward Trajectory Steering for Hamilton-Jacobi Reachability Analysis

arXiv:2608.11480v1 Announce Type: cross Abstract: Hamilton-Jacobi (HJ) reachability provides a mathematically rigorous framework for safe control of dynamical systems, but its practical application is

safetyarxiv-cs-lg

FQTree: Fine-grained Quantization and Hardware Generation of Boosted Decision Trees

arXiv:2608.12140v1 Announce Type: cross Abstract: Boosted decision trees (BDTs) are widely used in latency-critical applications, but efficient hardware deployment remains challenging. Existing design

safetyarxiv-cs-lg

GenFAR: A generalized representation of brain structure, derived from 49,246 multi-cohort MRIs via deep learning

arXiv:2608.12185v1 Announce Type: new Abstract: Deep learning models for neuroimaging have largely been developed for individual tasks, limiting knowledge transfer across applications. Here we introdu

HUGIN: Enhancing Vision-Language Planning for Autonomous Logistics Sorting

arXiv:2608.11692v1 Announce Type: new Abstract: Autonomous logistics sorting systems (ALSS) are an important industrial application of embodied AI, which requires joint planning over spatially disjoin

Koopman Representation of Nonlinear Virtual Environments in Kinesthetic Haptic Systems

arXiv:2608.11461v1 Announce Type: new Abstract: Rendering haptic feedback with nonlinear virtual environments (VEs) is important in many applications that require highly accurate force feedback. This

researcharxiv-cs-ro

Motion-as-Prompt: Enhancing Motion Reasoning in Multimodal Large Language Models via Motion-Guided Cross-Frame Visual Prompting

arXiv:2608.11655v1 Announce Type: cross Abstract: Motion-centric video reasoning is fundamental to interactive applications such as robotic manipulation and autonomous navigation. However, multimodal

Policy-as-logic for robust reasoning over rules

arXiv:2608.11905v1 Announce Type: new Abstract: In many practical applications of generative AI systems, from tax rules to airline baggage allowance, responses to natural language queries must respect

Reproducible canvas-aligned low-level patterns in somerandomllm-generated images and their possible relation to iterative editing artifacts [D]

I may have stumbled onto something interesting while trying to figure out a recurring artifact in ChatGPT image generation and editing (maybe applicable to other models as well?). It started with a ve

safetyr-machinelearning

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision

arXiv:2608.11564v1 Announce Type: new Abstract: Depth estimation from thermal images is highly valuable for robotic applications in adverse conditions, such as nighttime and rainy weather. Recent stud

Soft-Attention Improves Skin Cancer Classification Performance

arXiv:2105.03358v4 Announce Type: replace-cross Abstract: In clinical applications, neural networks must focus on and highlight the most important parts of an input image. Soft-Attention mechanism ena

TGRHuman: Text-Guided Realistic 3D Human Generation via Diffusion Renderer

arXiv:2608.12175v1 Announce Type: new Abstract: Realistic 3D human generation plays a crucial role in many graphics applications. However, current methods still struggle to generate high-quality human

Local Ai

UniGround: Universal 3D Visual Grounding via Training-Free Scene Parsing

arXiv:2603.08131v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) localizes objects from natural-language descriptions in 3D scenes and is fundamental to embodied AI applications. A

local-aiarxiv-cs-cv

A Convolutional Layer Activation Dimensionality Reduction for Out-of-Distribution and Adversarial Attack Detection Methods

arXiv:2608.10203v1 Announce Type: new Abstract: Despite the success of convolutional neural networks in image classification tasks and their general application in multi-modal models, their susceptibi

safetyarxiv-cs-cv

Automated Data Enrichment using Confidence-Aware Fine-Grained Debate among Open-Source LLMs for Mental Health and Online Safety

arXiv:2512.06227v3 Announce Type: replace Abstract: Real-world indicators play an important role in many Natural Language Processing (NLP) applications, such as life events for mental health analysis

safetyarxiv-cs-cl

Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantization

arXiv:2602.02035v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significant

agentsarxiv-cs-ai

Chain of Spatial Thoughts: Modality-Agnostic Spatial Grounding for Vision Language Models

arXiv:2608.10278v1 Announce Type: new Abstract: Spatial understanding is fundamental to embodied intelligence, underpinning applications such as robotic manipulation, embodied navigation, and autonomo

agentsarxiv-cs-cv

Closed-Loop LLM Co-Pilots for Digital Agriculture

arXiv:2608.09949v1 Announce Type: new Abstract: This study evaluates the application of Large Language Models (LLMs) in complex biological systems, evolving from data analysis to autonomous, AI-guided

Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits

arXiv:2608.10526v1 Announce Type: cross Abstract: Motivated by decentralized applications, we study cooperative multi-agent bandits in continuous (Lipschitz) action spaces when the Lipschitz constant

agentsarxiv-cs-ai

DIMOS: Disentangling Instance-level Moving Object Segmentation

arXiv:2606.12826v2 Announce Type: replace-cross Abstract: Moving instance segmentation (MIS) attracts increasing attention due to its broad applications in traffic surveillance, autonomous driving, an

Elbow Angle Guidance System Based on Surface Haptic Sensations Elicited by Lightweight Wearable Fabric Actuator

arXiv:2608.10404v1 Announce Type: cross Abstract: The demand for wearable haptic devices has rapidly increased for various applications. However, many haptic devices interfere with the wearer's activi

researcharxiv-cs-ro

Hierarchical Compositionality for An Assistive AI Agent

arXiv:2608.10330v1 Announce Type: new Abstract: AI agents are increasingly being developed to assist humans in various applications, and Large Language Models and other deep network architectures are

agentsarxiv-cs-ai

Hardware

How to Choose Full-Stack Observability for NVIDIA AI Factories

A full‑stack observability framework for NVIDIA AI factories links telemetry from compute, networking, storage, orchestration and application layers using specialized tools (DCGM, NVSM, UFM, NetQ, NMX

hardwarenvidia-developer

HQ-DM: Single Hadamard Transformation-Based Quantization-Aware Training for Low-Bit Diffusion Models

arXiv:2512.05746v3 Announce Type: replace Abstract: Diffusion models have demonstrated significant applications in the field of image generation. However, their high computational and memory costs pos

MIDAS: Mutual Information Disentanglement with Uncertainty-Aware Fusion for Incomplete Multimodal Sentiment Analysis

arXiv:2608.09986v1 Announce Type: new Abstract: Most existing multimodal sentiment analysis approaches assume access to complete multimodal inputs. However, real-world applications frequently encounte

Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure

arXiv:2606.17441v2 Announce Type: replace-cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and ex

researcharxiv-cs-ai

Rethinking LLM Verification: Evidence Structure, Uncertainty, and Selective Refinement

arXiv:2608.10725v1 Announce Type: new Abstract: Large language models (LLMs) often rely on shortcuts rather than systematic reasoning, raising safety concerns in medical applications. Allowing models

Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation

arXiv:2608.10932v1 Announce Type: cross Abstract: Understanding camera motion is fundamental to video perception, with applications in spatial intelligence and controllable video generation. Multimoda

A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Cameras

arXiv:2608.09520v1 Announce Type: new Abstract: In many autonomous applications requiring real-time localization, active marker-based systems are preferred due to their low latency and ease of deploym

agentsarxiv-cs-cv

Tutorials

Adaptive Symmetry Discovery for Dynamical System Identification

arXiv:2608.08091v1 Announce Type: cross Abstract: Dynamical systems model trajectory data generated by fixed underlying dynamics, with applications ranging from biology to physics. Especially in scien

tutorialsarxiv-cs-ai

BASIS: Breach-Aware Selective Prompt Injection Shielding with Prefill Attention Probes

arXiv:2608.08027v1 Announce Type: cross Abstract: Prompt injection is a critical security threat in large language model (LLM) applications, where attackers hijack model behavior by embedding maliciou

researcharxiv-cs-lg

Dense Point-to-Mask Optimization with Reinforced Point Selection for Crowd Instance Segmentation

arXiv:2604.01742v2 Announce Type: replace Abstract: Crowd instance segmentation is a crucial task with a wide range of applications, including surveillance and transportation. Currently, point labels

safetyarxiv-cs-cv

Efficient Human-Contact Representation for Human-Scene Interaction

arXiv:2608.09388v1 Announce Type: new Abstract: Human-scene interaction is an active research topic with several industrial applications in virtual reality, gaming, robotics, and surveillance. Despite

How to Ask the AI: A User Perspective Survey for Large Language Model Prompting

arXiv:2608.07494v1 Announce Type: cross Abstract: AI tools like ChatGPT and DeepSeek, powered by Large Language Models (LLMs), allow users to obtain instant and effective content responses simply by t

LEGO-Puzzles: How Good Are MLLMs at Multi-Step Spatial Reasoning?

arXiv:2503.19990v4 Announce Type: replace Abstract: Many real-world applications of spatial intelligence, such as robotic control, autonomous driving, and automated assembly, require spatial reasoning

Tutorials

Leveraging generative models to assist Monte Carlo sampling

arXiv:2608.07648v1 Announce Type: cross Abstract: Sampling high-dimensional probability distributions is a central task in scientific computing, with applications ranging from Bayesian inference to st

tutorialsarxiv-cs-lg

Med-CRAFT: An Information System for Explainable and Configurable Construction of Multimodal Medical QA Datasets

arXiv:2512.01045v2 Announce Type: replace Abstract: Data-intensive artificial intelligence applications increasingly rely on large-scale, high-quality, explainable, and reproducible datasets, yet the

researcharxiv-cs-ai

MotionCraft: Latent World Modeling with Sparse Attention for Visual Upscaling

arXiv:2608.08553v1 Announce Type: new Abstract: Video super-resolution (VSR) aims to recover high-fidelity high-resolution videos from low-resolution inputs and is central to applications ranging from

safetyarxiv-cs-cv

NeuroBreak: Unveil Internal Jailbreak Mechanisms in Large Language Models

arXiv:2509.03985v2 Announce Type: replace-cross Abstract: In deployment and application, large language models (LLMs) typically undergo safety alignment to prevent illegal and unethical outputs. Howev

Now in preview: The ChatGPT desktop app for Linux. Use ChatGPT, ChatGPT Work, and Codex where you already work and build, with your projects…

OpenAI released a preview of its new ChatGPT desktop application for Linux on August 11 2026. The app allows users to run ChatGPT, ChatGPT Work and Codex directly from their desktop, integrating with

model-releasesopenai--x

Population-Level Generative Modeling for Ranking Data

model-releasesarxiv-cs-lg

arXiv:2608.08422v1 Announce Type: cross Abstract: Ranking data arise in scientific and machine learning applications, including recommendation systems, information retrieval, voting, marketing, and AI

Predicting blood clot growth from sparse post-onset measurements with latent neural differential equations

model-releasesarxiv-cs-lg

arXiv:2608.08165v1 Announce Type: new Abstract: Computational models of blood clotting improve understanding of thrombus formation, but their clinical application remains limited because many model in