Search: “applications”

A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects

model-releasesarxiv-cs-ro

arXiv:2609.09403v1 Announce Type: new Abstract: In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning. Thi

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

AgentFairBench: Do LLM Agents Discriminate When They Act?

DGX agent

arXiv:2606.16723v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly take actions (screening applicants, recommending credit, triaging patients), yet fairness for LLMs is

model-releasesarxiv-cs-ai

10 Sept 2026

Industry

Amazon Quick is now generally available on desktop

Your teams get an AI assistant that handles real work while your data stays in your environment and your conversations stay private Today, the Amazon Quick desktop application is generally available o

industryaws-ml-blog

Beyond Weak Labels: Prompt-Guided Local Refinement for Weakly Supervised Water Segmentation in High-Resolution Multispectral Imagery

arXiv:2609.10371v1 Announce Type: new Abstract: High-resolution water mapping supports environmental monitoring and related applications, but accurate pixel-level labels are difficult and costly to pr

Complexity and Scale in AI-Assisted Workflow Management: A Federated Learning Case Study

arXiv:2606.18425v2 Announce Type: replace-cross Abstract: Federated learning over medical images is a demanding workflow application. Each round fans out across parallel client jobs and converges on a

Do speech foundation models really learn words?

arXiv:2609.10434v1 Announce Type: new Abstract: Self-supervised speech foundation models are now used in a wide array of downstream applications, including traditional speech recognition and as the ba

tutorialsarxiv-cs-cl

Edu-QuRating: Multi-Dimensional Educational Data Curation with Distilled Pairwise Judgements

model-releasesarxiv-cs-cl

arXiv:2609.09425v1 Announce Type: new Abstract: Educational data filters have become a practical way to improve language-model pre-training, but most filters treat educational value as a single scalar

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

arXiv:2609.10018v1 Announce Type: new Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these dep

Evidence-Aligned Entity Verification for Hallucination Detection in Retrieval-Augmented Generation

arXiv:2609.08267v1 Announce Type: new Abstract: Hallucination detection is crucial for large language models (LLMs), as hallucinated content creates significant barriers in applications requiring fact

safetyarxiv-cs-ai

Explainable Token-level Noise Filtering for LLM Fine-tuning Datasets

arXiv:2602.14536v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have seen remarkable advancements, achieving state-of-the-art results in diverse applications. Fine-tuning, an im

researcharxiv-cs-ai

Improving Cross-Lingual Token Representations by Adding a Pinch of SALT

arXiv:2609.09953v1 Announce Type: new Abstract: Cross-lingual sentence encoders enable scalable transfer across hundreds of languages, powering applications such as translation mining and zero-shot le

safetyarxiv-cs-cl

Kernel-Complexity Edge Sanitization for Training-Free Defense against Structural Graph Attacks

arXiv:2609.09698v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain highly vulnerable to adversarial attacks that

researcharxiv-cs-lg

Learning with Covariance Matrices: Principal Component Analysis Meets Learning with Graphs

arXiv:2609.10490v1 Announce Type: new Abstract: This feature article provides an overview of the theoretical foundations for coVariance neural networks (VNNs), i.e., graph neural networks (GNNs) opera

tutorialsarxiv-cs-lg

MLLMs Hallucinate when Information Distribution Drifts in Synergy Heads

arXiv:2609.09206v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) often struggle with hallucinations, thus hindering their reliable practical applications. Existing attention-

researcharxiv-cs-cl

ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making

arXiv:2609.07601v1 Announce Type: cross Abstract: The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks

Personalized Execution Time Optimization for Billion-Scale Scheduled Jobs

arXiv:2203.06158v3 Announce Type: replace Abstract: Scheduled batch jobs are widely used on asynchronous computing platforms to execute enterprise applications such as promotional notifications and ca

safetyarxiv-cs-lg

Spot-the-shift: Evaluating Grounded Image Difference Captioning of Long-term Changes

arXiv:2609.10356v1 Announce Type: new Abstract: Long-term change understanding from images of the same place revisited over time is a challenging task with applications in map maintenance and urban in

SRD-GUARD: A Defense Framework of LLMs via Semantic Rewriting and Joint Multi-Model Scoring for Latent Intent Exposure

arXiv:2609.06540v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical applications, yet jailbreak attacks can conceal harmful intent through role-

The Audit Decides the Verdict: Instrument Effects Rival Demographic Bias in LLM Decision Audits

arXiv:2609.09048v1 Announce Type: cross Abstract: Whether a language model looks demographically biased can depend on how the audit asks its question. A charitable-aid benchmark reports that the same

The Role of Gradient Modification in Heavy-Tailed Nonconvex Stochastic Min-Max Optimization

arXiv:2609.06064v1 Announce Type: cross Abstract: Stochastic min-max optimization has attracted increasing attention due to its applications in modern machine learning, while existing theoretical stud

researcharxiv-cs-ai

TimeCues Studio: A Workspace for Music Annotation and Algorithm Prototyping

arXiv:2609.10338v1 Announce Type: cross Abstract: Multimedia applications require precise music annotation-labeled positions, segments, or loops-placed by hand or algorithmically. Machine-learning alg

researcharxiv-cs-lg

A Cloud-Based Hybrid Model for Real-Time Detection of BRTA-Approved Licence Plates Using YOLO Tiny and Haar Cascade

arXiv:2609.06507v1 Announce Type: new Abstract: Accurate vehicle license plate detection is essential for applications such as intelligent transportation systems, toll collection, parking management,

Accelerating Diffusion Transformers with Gaussian Process Rectified Feature Cache

arXiv:2609.05981v1 Announce Type: new Abstract: Diffusion Transformers have become the dominant paradigm in generative AI, but their high computational costs severely hinder real-time applications. Pr

AD-FM: Multimodal LLMs for Anomaly Detection via Multi-Stage Reasoning and Fine-Grained Reward Optimization

arXiv:2508.04175v2 Announce Type: replace Abstract: While Multimodal Large Language Models (MLLMs) demonstrate remarkable capabilities across diverse domains, their application to specialized anomaly

AGSA-Net: Abundance-Guided Self-Attention Network for Spectral Unmixing-Aware Hyperspectral Remote Sensing Image Classification

arXiv:2609.06359v1 Announce Type: new Abstract: Hyperspectral image (HSI) classification plays a vital role in remote sensing applications, including agriculture, environmental monitoring, and urban a

ArmPoser: Real-Time, Calibration-Free Arm Pose Estimation from Smartwatch IMU

arXiv:2609.08806v1 Announce Type: new Abstract: Arm pose estimation enables applications in fitness, extended reality input, rehabilitation, and life logging. Prior smartwatch-based approaches rely on

safetyarxiv-cs-cv

ARNAI: Artifact Removal Network based on Autoencoding and Inpainting for Robust Spinal Image Segmentation and Measurement

arXiv:2609.07013v1 Announce Type: new Abstract: Purpose: This study aims to develop an AI framework applicable for postoperative imaging for automated measurement of spinopelvic parameters on radiogra

Bigger Text Encoders Can Hurt CLIP Zero-Shot Performance

arXiv:2609.05730v1 Announce Type: new Abstract: Contrastive Language-Image Pretraining (CLIP) is a building block of many machine learning applications. Scaling laws have guided resource allocation fo

ComVLA: Communication-Aware Split Inference for VLA Models in 6G-Connected Robotics

model-releasesarxiv-cs-ro

arXiv:2609.07838v1 Announce Type: new Abstract: Connected robotics is an emerging 6G application where mobile robots follow natural-language instructions to manipulate physical objects. The Vision-Lan

Cost-Optimal LLM Routing with Limited User Feedback under User Satisfaction Guarantees

model-releasesarxiv-cs-lg

arXiv:2606.19376v2 Announce Type: replace Abstract: Inference costs for large language model (LLM) applications are rapidly growing, driven by surging demand and rising infrastructure cost. Users expe

Cross-modal learning for SAR target recognition using optical vision foundation models

arXiv:2609.07753v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather op

safetyarxiv-cs-cv

CrowdTraj: A Benchmark for Dense Crowd Trajectory Prediction in Realistic Crowded Environments

arXiv:2609.07685v1 Announce Type: new Abstract: In real-world applications, pedestrian trajectory prediction models rely on inputs from detection and tracking systems. Prior trajectory prediction benc

Do Input-Level Defenses Transfer to Observation-Level Attacks on VideoLLMs?

arXiv:2609.08331v1 Announce Type: new Abstract: Video Large Language Models (VideoLLMs) are increasingly deployed in safety-critical applications such as content moderation and video analytics. To pro

EMBLEM: Enhancing Multi-script Table Detection through Masking

arXiv:2609.08330v1 Announce Type: new Abstract: Table detection is a core task in document analysis, supporting downstream applications such as information retrieval, document reconstruction, and visu

researcharxiv-cs-lg

Enterprise-grade PostgreSQL with AlloyDB Omni RPM Orchestrator is generally available

model-releasesgoogle-cloud-ai

We are thrilled to announce the general availability of the AlloyDB Omni Red Hat RPM orchestrator, that brings production-ready security, resiliency, and low-downtime operations to PostgreSQL workload

Hardware

EStream: Fast and Memory-Efficient MoE Prefill through Expert Virtualization on Mobile NPUs

arXiv:2609.06551v1 Announce Type: cross Abstract: Mobile vendors and application developers increasingly deploy LLMs on smartphones for diverse prefill-only services. Yet current systems rely mainly o

hardwarearxiv-cs-lg

Generating from Discrete Distributions Using Diffusions: Insights from Random Constraint Satisfaction Problems

model-releasesarxiv-cs-lg

arXiv:2603.20589v2 Announce Type: replace Abstract: Generating data from discrete distributions is important for a number of application domains including text, tabular data, and genomic data. Several

Geodesic-informed Generative Diffusion Model For Topology-preserved Image Video Generation

arXiv:2609.08153v1 Announce Type: cross Abstract: Generative diffusion models have emerged as a class of powerful techniques for various imaging applications, including but not limited to synthesis, r

tutorialsarxiv-cs-cv

Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat

arXiv:2609.07557v1 Announce Type: new Abstract: 3D Gaussian Splatting has recently revolutionised novel view synthesis as well as many other 3D vision methods and applications. Drawing inspiration fro

Hyperspectral Trajectory Image for Multi-Month Trajectory Anomaly Detection

arXiv:2603.25255v2 Announce Type: replace Abstract: Trajectory anomaly detection underpins applications from fraud detection to urban mobility analysis. Dense GPS methods preserve fine-grained evidenc

Agents

Input-to-State Stability Framework for Fully Distributed Primal-Dual Dynamics for Quadratic GNEPs Without Multiplier Consensus

arXiv:2609.06983v1 Announce Type: cross Abstract: Generalized Nash Equilibrium Problems (GNEPs) often arise in multi-agent engineering applications that require distributed algorithms. Unlike traditio

agentsarxiv-cs-lg

Learning Metamaterial Eigenmodes with Wavelet-Encoded Fourier Neural Operators

arXiv:2609.08102v1 Announce Type: new Abstract: Machine learning surrogates based on neural operators have shown broad applicability in solving forward PDE problems. However, eigenvalue problems, in w

tutorialsarxiv-cs-lg

Syntheses

Wiki Lint Report — 2026-09-09

linthealth-checkautomated

Automated lint: 12 errors, 53990 warnings, 3 info

Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation

arXiv:2609.08084v1 Announce Type: new Abstract: Monocular depth estimation is a ubiquitous yet highly ill-posed computer vision task, with downstream applications in scene reconstruction, computationa

Online Signature Verification Using Augmented Path Signature and T-Mamba

arXiv:2609.08276v1 Announce Type: cross Abstract: Handwritten signature verification is vital for personal authentication across commercial and financial applications. Although deep learning methods a

Agents

Orchid Security gives enterprises a kill switch for rogue AI agents

Identity security startup Orchid Security Inc. today added identity drift detection and application-level kill switches for artificial intelligence agents to its Identity Control Plane. The controls a

agentssiliconangle

PASTEL: Panoramic Alignment for Monocular 4D Scene Reconstruction

arXiv:2609.06099v1 Announce Type: new Abstract: Reconstructing 4D scenes from casually captured monocular video is vital for applications in virtual reality (VR) and embodied AI. Recent advances in 4D

safetyarxiv-cs-cv

PatchFormer: A Patch-Based Time Series Foundation Model with Hierarchical Masked Reconstruction and Cross-Domain Transfer Learning for Zero-Shot Multi-Horizon Forecasting

model-releasesarxiv-cs-lg

arXiv:2601.20845v2 Announce Type: replace Abstract: Time series forecasting is a fundamental problem with applications in climate, energy, healthcare, and finance. Many existing approaches require dom