Search: “applications”

arXiv:2608.22631v1 Announce Type: new Abstract: Terminal agents are a compelling application of large language models (LLMs), with the potential to integrate deeply into users' daily workflows. Reinfo

agentsarxiv-cs-lg

Loopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding

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DGX agent

arXiv:2608.23090v1 Announce Type: new Abstract: Looping videos are essential for practical applications such as web graphics, game development, and social media. However, existing approaches typically

model-releasesarxiv-cs-cv

25 Aug 2026

MedReaMM: Evaluating Large Multimodal Models on Expert-Level Clinical Diagnostic Synthesis

model-releasesarxiv-cs-cv

arXiv:2608.22323v1 Announce Type: new Abstract: The application of Large Language Models (LLMs) to diagnostic decision-making has garnered growing interest. However, existing benchmarks largely focus

Memory-Enhanced Neural Solvers for Routing Problems

arXiv:2406.16424v4 Announce Type: replace Abstract: Routing Problems are central to many real-world applications, yet remain challenging due to their (NP-)hard nature. Amongst existing approaches, heu

Minimum Bisection Problem: Machine Learning-Based Penalty Parameter Tuning for Optimization on Quantum Annealers

arXiv:2509.19005v2 Announce Type: replace-cross Abstract: The Minimum Bisection Problem is a fundamental, computationally hard graph partitioning problem with applications in parallel computing, netwo

Misanthrope: A Privacy-Preserving Keypoint Detector

arXiv:2608.23012v1 Announce Type: new Abstract: Image matching is a core component of applications such as Simultaneous Localization and Mapping (SLAM), Visual Localization, and Structure from Motion

local-aiarxiv-cs-cv

Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning

arXiv:2505.15798v2 Announce Type: replace Abstract: Certifying the IID generalisation ability of deep networks is the first of many requirements for trusting AI in high-stakes applications from medici

Multimodal Injury Risk and Performance Prediction in Tennis Using Weighted Ensemble Learning

arXiv:2608.21530v1 Announce Type: new Abstract: Machine learning has had a positive impact on the sports industry, with one of its most promising applications being the prediction of athlete performan

researcharxiv-cs-lg

No One Model Catches Every Harm: Benchmarking Content Moderation Across Safety Scenarios

arXiv:2608.21775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications, yet they remain vulnerable to generating harmful content. From advers

safetyarxiv-cs-cl

QIRL: Optimized Question-Image Relation Learning for Bias-Robust Visual Question Answering

arXiv:2504.03337v2 Announce Type: replace Abstract: Existing bias mitigation methods for Visual Question Answering (VQA), a typical Artificial intelligence application, endure two main limitations. Fi

safetyarxiv-cs-cv

Reasoning Meets Personalization: Unleashing the Potential of Large Reasoning Model for Personalized Generation

arXiv:2505.17571v2 Announce Type: replace Abstract: Personalization is a critical task in modern intelligent systems, with applications spanning diverse domains, including interactions with large lang

safetyarxiv-cs-cl

Robustness of IR Models to Collection Growth

arXiv:2608.23419v1 Announce Type: cross Abstract: Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with d

researcharxiv-cs-cl

Scalable quantum simulation of continuous-time generative models via tensor networks

arXiv:2608.21700v1 Announce Type: cross Abstract: Continuous-time flow and diffusion models are widely used across many application domains, from large-scale deployment in computer vision and protein

Tutorials

SemanticXR: Low Power and Real-time Queryable Semantic Mapping with an Object-Level Device-Cloud Architecture

arXiv:2606.12849v2 Announce Type: replace-cross Abstract: Semantic mapping is a core service that enables grounded interactions in emerging Extended Reality (XR) applications such as AI assistants. De

tutorialsarxiv-cs-cv

Software Frameworks for Explainable AI in Time Series Classification: A Systematic Review

arXiv:2608.21449v1 Announce Type: new Abstract: Time series arise in a wide range of application domains and are analyzed using machine learning in decision-critical settings. Time series classificati

Switched Turn-based Adaptive Source Seeking Strategy using Estimation and Information-driven Direction of Improvement

arXiv:2608.23068v1 Announce Type: new Abstract: Source seeking arises in applications such as gas leak localization, radiation monitoring, and environmental surveillance, where the origin of an unknow

researcharxiv-cs-ro

Agents

TessIndex: Capability Verified Identity System for the Agent Economy

arXiv:2608.21942v1 Announce Type: new Abstract: Software systems have traditionally been organized around applications where human users act as principal decision-makers. Recent developments in agenti

agentsarxiv-cs-ai

Hardware

The Communication Map of a Transformer

arXiv:2608.22007v1 Announce Type: cross Abstract: The components of a transformer communicate by writing to and reading from a shared residual stream, and mechanistic interpretability has mapped these

hardwarearxiv-cs-cl

Towards Alias-Free 4D Gaussian Representations with Motion-Aware Filtering

arXiv:2608.21828v1 Announce Type: new Abstract: Novel-view synthesis of dynamic scenes, crucial for AR/VR applications, remains a challenging problem. Recent methods adapt representations like 3D Gaus

local-aiarxiv-cs-cv

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding

model-releasesarxiv-cs-cv

arXiv:2607.14935v2 Announce Type: replace Abstract: Recent advances in video understanding have spanned motion, long video, and streaming interaction, driving this field toward real-world applications

Anchoring Instruction Outside Mask: Exact Reference Caching for Efficient In-Context Diffusion Transformers

arXiv:2608.21229v1 Announce Type: new Abstract: Omnimodal generation is central to a wide range of content creation and editing applications. In-context conditioning is essential to this paradigm. It

safetyarxiv-cs-cv

Building and Evaluating a Synthetic Bengali Speech Resource for Telecom Customer Care

model-releasesarxiv-cs-cl

arXiv:2608.20346v1 Announce Type: new Abstract: Speech systems used in customer-facing applications often require domain-specific language coverage. We present a synthetic Bengali speech dataset for t

CoST: Semantic-Aware Urban Understanding via Spatial-Temporal Alignment

arXiv:2608.21041v1 Announce Type: cross Abstract: Geospatial representation learning from satellite imagery is a fundamental problem for large-scale urban analysis and real-world applications. Despite

Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation

arXiv:2505.16222v2 Announce Type: replace Abstract: With the growing use of large language models(LLMs) as evaluators, their application has expanded to code evaluation tasks, where they assess the co

safetyarxiv-cs-cl

Knowledge-Graph-Gated Defactualization for Style-Controllable and Fact-Preserving Generation in Agentic Conversational AI

model-releasesarxiv-cs-ai

arXiv:2608.20393v1 Announce Type: cross Abstract: Agentic large language models (LLMs) deployed in fact-sensitive applications such as customer support must simultaneously preserve factual correctness

Ontology-supported AI Model and Dataset Management

arXiv:2608.21224v1 Announce Type: new Abstract: Recently, there has been a great deal of research into improving AI methods and their application. The main focus is on tracking progress, enabling tran

Structure is information: structural identifiability mappings for machine learning with partially observed dynamical systems

arXiv:2502.04131v2 Announce Type: replace Abstract: The successful application of modern machine learning for time series classification is often hampered by limitations in quality and quantity of ava

When Looks Do Not Lie: Discourse Structure Guided In-Context Learning for Faithful Diagram Generation

arXiv:2601.20476v2 Announce Type: replace Abstract: GenAI is widespread in educational applications; however, it is known to generate content with intrinsic and extrinsic hallucination. We introduce a

researcharxiv-cs-cl

A Locally Tokenized Generative Model for Robust Time-Series Watermarking

arXiv:2608.19727v1 Announce Type: cross Abstract: Watermarking is a central tool for provenance in generative models, yet its application to multivariate time series remains hindered by reliability fa

local-aiarxiv-cs-ai

A Repeated Measurements Approach to SoH Battery Modelling of Cyclic Aged Data in a Laboratory Environment

arXiv:2608.19879v1 Announce Type: cross Abstract: This document describes the application of a first order linearised nonlinear repeated measurements approach to the analysis of battery cell ageing pr

Enforcing LLM Safety through DMD-based Classification of Prompt-Response Embedding Dynamics

model-releasesarxiv-cs-ai

arXiv:2608.19579v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in high-stakes applications, yet their tendency to generate toxic, harmful, or policy-violating c

Exact Algebraic Computation of Learning Coefficients for Two-Dimensional Singular Models

arXiv:2608.20183v1 Announce Type: new Abstract: Classical information criteria such as the Bayesian Information Criterion (BIC) rely on regularity assumptions that break down for singular models, lead

local-aiarxiv-cs-lg

Heteroscedastic Neural Surrogate Modeling for Robust and Rapid Bayesian Inference in Fusion Plasma Diagnostics

arXiv:2608.19377v1 Announce Type: cross Abstract: Bayesian inference via Markov Chain Monte Carlo (MCMC) provides effective parameter estimation, but its real-time application in complex physical syst

Holtercare-Bench: A Multimodal Benchmark for Evaluating Long-Term Dynamic ECG Analysis

arXiv:2608.19297v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) excel in medical applications, most of them favor static images or short-term signals. In the critical fi

Learning Early-to-Final Solution Consistency for MILP Acceleration

arXiv:2608.19953v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) is a fundamental problem class in operations research and combinatorial optimization, with broad applications to

MILD: Tractable Terrain Modeling for Learning Improved Bipedal Locomotion on Deformable Surfaces

arXiv:2608.19955v1 Announce Type: new Abstract: Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold

researcharxiv-cs-ro

Multi-Source Wasserstein Distributionally Robust Graph Learning

arXiv:2608.19914v1 Announce Type: new Abstract: Network topology inference from graph signals is central to graph signal processing with applications in neuroscience, sensor, and social networks. In p

safetyarxiv-cs-lg

Allocating Recurrent Compute in Looped Language Models

arXiv:2608.18230v1 Announce Type: new Abstract: Looped language models improve reasoning and knowledge manipulation by applying shared computation repeatedly. Existing systems usually repeat an entire

researcharxiv-cs-lg

Comment-level Topic Drift Analysis in the Reddit Corpus

arXiv:2608.19133v1 Announce Type: new Abstract: We present a novel application of embedding-based dynamic topic modeling techniques to detect and quantify topic drift at the comment level in a massive

researcharxiv-cs-cl

Coupled-cluster molecular properties across the main group that extrapolate beyond training size

arXiv:2608.18346v1 Announce Type: cross Abstract: Coupled-cluster theory defines the accuracy standard for molecular electronic-structure properties but scales too steeply for routine application, whe

local-aiarxiv-cs-ai

Hardware

Depth Anything V4: Dynamic 4D Scene Reconstruction via Riemannian Flow Matching on 4D Gaussian Splatting

arXiv:2608.18388v1 Announce Type: new Abstract: We present Depth Anything V4 (DAV4), a framework for dynamic 4D scene reconstruction from monocular video. Our key contribution is the application of Ri

hardwarearxiv-cs-cv

Evaluation of Image Matching Methods for Visual Odometry on UAVs

arXiv:2608.18624v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are becoming a powerful tool for many environmental monitoring and transport applications. Yet, their reliance on Global

researcharxiv-cs-cv

extsc{TestifAI}: Tomography-Based Testing for Deep Learning Systems

arXiv:2608.18900v1 Announce Type: new Abstract: As AI systems are increasingly deployed in safety-critical application domains (e.g., autonomous driving), associated risks increase too. Deep learning

Flama: a Python framework for development and deployment of production-ready APIs, machine learning, and LLM services

arXiv:2608.18733v1 Announce Type: cross Abstract: We present Flama, an open-source Python framework for developing and deploying production-ready web APIs, machine learning services, and large-languag

local-aiarxiv-cs-ai

`From Prompt to Perturbation': An Adaptive Framework for Voice-Based Jailbreaks on Audio LLMs

arXiv:2502.00735v4 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly integrated into audio-based applications, growing concerns have emerged regarding their vulne

Generalized Audio-Driven Synthesis of Precise Drummer Motion

arXiv:2608.19055v1 Announce Type: new Abstract: Music-driven character animation enables and enhances transformative applications in entertainment and interactive education. However, synthesizing real

safetyarxiv-cs-cv

Agents

How AlloyDB ScaNN scales vector search to 10 billion vectors

To satisfy the demands of enterprise-grade agentic AI applications, underlying vector databases often struggle to scale effectively as modern use cases can scale to billions of vectors. As a fully man

agentsgoogle-cloud-ai

Institutional Prestige as Geographic Bias in Large Language Models: Evidence from Three Factorial Experiments with Bootstrap Confidence Intervals

arXiv:2608.18107v1 Announce Type: cross Abstract: We investigate whether large language models (LLMs) systematically discriminate in candidate evaluations based on applicant name ethnicity and/or inst