Search: “applications”

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

12 Aug 2026

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

DGX agent

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

model-releasesarxiv-cs-cv

12 Aug 2026

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

12 Aug 2026

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

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

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

Population-Level Generative Modeling for Ranking Data

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

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

Recurrent Neural Networks Beyond Time: Learning from Multiple Ordered Projections

arXiv:2608.09690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) are widely used for sequence learning, yet their application is commonly associated with temporal data, although recurr

RoSE: A Robotic Soft Esophagus for Endoprosthetic Stent Testing

arXiv:2608.09891v1 Announce Type: new Abstract: Soft robotic systems are well suited for developing devices for biomedical applications. A bio-mimicking robotic soft esophagus (RoSE) is developed as a

researcharxiv-cs-ro

Software Engineering for and with GUI Agent

arXiv:2608.09278v1 Announce Type: cross Abstract: GUI agents have advanced rapidly, producing a growing body of frameworks, benchmarks, and applications. However, this growth has outpaced the maturity

Temporal Misgrounding in Legal RAG: A Versioned-Corpus Benchmark for French Tax Law

arXiv:2608.09393v1 Announce Type: cross Abstract: We identify and quantify temporal misgrounding: the systematic retrieval and citation of the currently in-force version of a legal article when the ap

The Voiceprint Fallacy: Why Voices Are Not Unique Biometric Imprints

arXiv:2608.07980v1 Announce Type: cross Abstract: In recent years, the term voiceprint has regained attention, particularly in technological applications and policy-making contexts, often carrying the

safetyarxiv-cs-cl

Tutorials

Transformer Explainer: Learning LLM Transformers with Interactive Visual Explanation and Experimentation

arXiv:2408.04619v2 Announce Type: replace-cross Abstract: The Transformer architecture underpins modern large language models powering state-of-the-art text generation and AI applications. However, it

tutorialsarxiv-cs-ai

Beyond Fluency: A Clinical Benchmark and Anomaly-Enhanced Baseline for Spine MRI Report Generation

arXiv:2608.07117v1 Announce Type: new Abstract: Radiology reporting is time-consuming and subject to inter-rater variability, making automated report generation an attractive clinical application for

Cascade: Exploiting SLO-Aware latency budget for fair and high goodput LLM inference serving

arXiv:2608.06557v1 Announce Type: cross Abstract: The reasoning and agentic capabilities of large language models have expanded the range of applications they support, from short interactive exchanges

safetyarxiv-cs-lg

Debias in Text, Believe Your Eyes: Text-Anchored Cross-Modal Transfer for Visual Counter-Commonsense Reasoning

arXiv:2608.06938v1 Announce Type: cross Abstract: The visual reasoning ability of multimodal large language models (MLLMs) is crucial for downstream applications, particularly counter-commonsense reas

Deep Evidential Regression for Sparse Forest Height Estimation from Multimodal Satellite Imagery

arXiv:2608.06406v1 Announce Type: new Abstract: Accurate estimation of forest height from satellite imagery is essential for applications such as carbon accounting, biodiversity monitoring, and ecosys

Online Conformal Prediction Beyond Feedback

arXiv:2608.07139v1 Announce Type: new Abstract: Uncertainty quantification is essential when deploying machine learning models in safety-critical applications. Online conformal prediction (OCP) provid

safetyarxiv-cs-lg

Probing Visual Concepts in Lightweight Vision-Language Models for Automated Driving

arXiv:2603.06054v2 Announce Type: replace-cross Abstract: The use of Vision-Language Models (VLMs) in automated driving applications is becoming increasingly common, with the aim of leveraging their r

agentsarxiv-cs-ai

Suppress and Diversify: Refining Robust Pathways for Corruption Robustness

arXiv:2608.06712v1 Announce Type: new Abstract: Model robustness against natural image corruptions is essential for safety-critical applications. While existing methods primarily focus on implicit rep

Theoretical Foundations of Communication-Efficient, Robust, and Practical Distributed and Federated Optimization

arXiv:2608.06563v1 Announce Type: new Abstract: Machine learning and optimization have advanced together, with practical demands motivating new theory and theoretical breakthroughs enabling new applic

A Unified Risk View of Uncertainty: Posterior Risk for Disentanglement and Evaluation Beyond Proxies

arXiv:2608.05995v1 Announce Type: new Abstract: Reliable uncertainty estimates are critical in safety-sensitive applications, where understanding the sources of predictive uncertainty is essential. Th

An Inertial Block Proximal Linearized Method with Adaptive Momentum for Nonconvex and Nonsmooth Optimization

arXiv:2608.05502v1 Announce Type: cross Abstract: In this paper, we consider a class of multiblock nonconvex nonsmooth optimization problems, which covers many applications such as the analysis of pre

Audio-to-Score Transcription using Pre-trained Features, Data Augmentation, and the New SheetSage-A2S Dataset

arXiv:2608.06165v1 Announce Type: cross Abstract: Existing audio-to-score (A2S) systems primarily focus on classical music, and the application to popular music remains underexplored. This paper first

DREAM: LLM-based Dynamic Role-playing via Event-Aware Memory Graph

arXiv:2608.05170v1 Announce Type: cross Abstract: Role-playing agents (RPAs) have emerged as a key application of large language models, enabling immersive and high-fidelity character simulation. Accu

Local Ai

EdgeXpert: An Edge Device for Memory-Efficient LLM Inference with Mixture-of-Experts and Speculative Decoding

arXiv:2608.05303v1 Announce Type: cross Abstract: On-device deployment of Large Language Models (LLMs) has become essential for personalized edge applications. A primary bottleneck is external memory

local-aiarxiv-cs-cl

Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising

arXiv:2510.05589v3 Announce Type: replace-cross Abstract: Effective time series forecasting enables various real-world applications, benefiting from the proliferation of mobile devices. However, the v

LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models

arXiv:2608.05706v1 Announce Type: new Abstract: World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied int

safetyarxiv-cs-cv

Multi-Agent Transformer for Queue-Level XR Traffic Scheduling in TSN Networks

arXiv:2608.05340v1 Announce Type: cross Abstract: Time-Sensitive Networking (TSN) and Mobile Edge Computing (MEC) hold strong potential for enabling ultra-reliable low-latency communication for time-s

agentsarxiv-cs-ai

One Leak Away: How Pretrained Model Exposure Amplifies Jailbreak Risks in Finetuned LLMs

arXiv:2512.14751v3 Announce Type: replace-cross Abstract: Finetuning pretrained large language models (LLMs) has become the standard paradigm for developing downstream applications. However, its secur

Shapes from Examples: Foundations of Shape Learning in Recursive SHACL

arXiv:2607.27934v2 Announce Type: replace Abstract: SHACL shapes enable data graph validation, making automatic shape learning essential for knowledge graph applications. We investigate the well-known

SkillTFM: Gated Skill Evolution for Training-Free Adaptation of Tabular Foundation Models

arXiv:2608.06137v1 Announce Type: new Abstract: Tabular data are ubiquitous in real-world applications and are crucial for data-driven prediction and decision-making across science, industry, finance,

TS-RAG: Retrieval Augmented Generation for Time Series Forecasting

arXiv:2608.06223v1 Announce Type: new Abstract: While deep learning models, particularly transformer-based architectures, have shown impressive performance in time series forecasting, the application

Worst-Case Distance-Aware Error Bounds for Neural Networks

arXiv:2510.22021v3 Announce Type: replace Abstract: Safety-critical applications of machine learning require uncertainty estimates that support reliable worst-case analysis. Neural networks (NNs) prov

safetyarxiv-cs-lg

A Chain Is Only as Strong as Its Weakest Link: A Scoping Review of System Integration Audits in AI

arXiv:2608.04921v1 Announce Type: cross Abstract: As AI systems become increasingly integrated into diverse interfaces and applications, model-centric audits are insufficient to address risks arising

AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering

arXiv:2411.04440v1 Announce Type: cross Abstract: Protein engineering is important for biomedical applications, but conventional approaches are often inefficient and resource-intensive. While deep lea

agentsarxiv-cs-ai

Local Ai

Beyond Motion Cues and Structural Sparsity: Revisiting Small Moving Target Detection

arXiv:2509.07654v2 Announce Type: replace Abstract: Small moving target detection is crucial for many defense applications but remains highly challenging due to low signal-to-noise ratios, ambiguous v

local-aiarxiv-cs-cv

CheckOne: Lightweight Fault Detection and Mitigation for Vision Transformers

arXiv:2608.04035v1 Announce Type: cross Abstract: The wide adoption of Vision Transformers (ViTs) in safety-critical applications raises reliability concerns related to hardware faults. Algorithm-Base

Exo2EgoPose: Leveraging Exocentric Demonstrations for Vision-Language guided Egocentric 3D Hand Pose Forecasting

arXiv:2607.15890v2 Announce Type: replace Abstract: Perceiving multimodal cues and forecasting fine-grained actions from an egocentric (Ego) perspective is vital for applications like robot manipulati

researcharxiv-cs-cv