Search: “applications”

Finite-Time Concentration and Convergence Rates for Projected Two-Time-Scale Stochastic Approximation with Markov Noise

arXiv:2609.34791v1 Announce Type: cross Abstract: We study finite-time concentration and convergence rates for projected two-time-scale stochastic approximation driven by a controlled Markov chain. Th

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From Dual Tracking to Clipping: Provably Faster Distributionally Robust Multi-Objective Optimization

DGX agent

arXiv:2605.05660v2 Announce Type: replace Abstract: Multi-objective optimization (MOO) has received growing attention in applications that require learning under multiple criteria. However, most exist

safetyarxiv-cs-lg

29 Sept 2026

GeoGAE: Scalable Graph-Level Autoencoding via Hyperball Cloud Representations

arXiv:2609.35527v1 Announce Type: new Abstract: Embedding structured objects into Euclidean spaces has enabled a wide range of successful machine learning applications. Such objects include words, doc

Handwritten Digit Leakage from Smartphone Motion Sensors Across Unseen Users and Phone Models

arXiv:2609.32117v1 Announce Type: new Abstract: Smartphone motion sensors support interactive applications, but their readings may also reveal touchscreen input beyond their intended use. Assuming kno

Hyperbolic Manifold Constrained Tabular Neural Network

arXiv:2607.09710v2 Announce Type: replace Abstract: Tabular prediction is central to a wide range of real-world applications. Tabular data typically contain heterogeneous features as well as rich and

Tutorials

Lagrangian and Hamiltonian Neural Networks With a Dissipative System

arXiv:2609.31988v1 Announce Type: new Abstract: We investigate the applicability of Lagrangian and Hamiltonian Neural Network models to a dissipative system that has explicit time dependence in its La

tutorialsarxiv-cs-lg

Last-Iterate Guarantees for Online Reinforcement Learning in Structured Constrained MDPs

arXiv:2609.32933v1 Announce Type: new Abstract: In safety-critical applications, deployment uses a single policy, whose performance and constraint satisfaction should hold directly rather than only fo

Learning Geometry-Aware Virtual Fixtures From Sparse Demonstrations

arXiv:2609.32958v1 Announce Type: new Abstract: In many teleoperation applications, collecting a large number of demonstrations as required for traditional probabilistic learning from demonstration (L

researcharxiv-cs-ro

Lightweight Wrappers for Adapting Time Series Foundation Models to Regional Drought Forecasting

arXiv:2607.17511v2 Announce Type: replace Abstract: Large Time Series Foundation Models (TSFMs) demonstrate strong zero-shot forecasting capabilities across diverse domains. However, their application

local-aiarxiv-cs-lg

Loop Dropout: Regularizing Shared Updates in Looped Language Models

arXiv:2609.34218v1 Announce Type: new Abstract: Looped language models separate computational depth from parameter count by repeatedly applying the same transformer block. Adapting these models requir

MASTEST: A LLM-Based Multi-Agent System For Testing RESTful APIs

arXiv:2511.18038v2 Announce Type: replace-cross Abstract: Testing RESTful API is increasingly complicated but indispensable to quality assurance of cloud-native applications. This paper reports a mult

Tutorials

Observability-Informed Optimal Sensor Placement for Soft Robots

arXiv:2609.33681v1 Announce Type: new Abstract: This paper presents the application and experimental evaluation of a systematic method for optimal sensor placement in soft robots. Existing methods eit

tutorialsarxiv-cs-ro

P4Q: Co-designing Token Pruning and Quantization for Vision-Language Model Acceleration

arXiv:2609.34867v1 Announce Type: new Abstract: Vision language models have achieved strong performance across a wide range of multimodal applications, yet their substantial computational and memory c

PolyTopoBench: A Benchmark for Complex Vector Polygon Generation from Remote Sensing Imagery

model-releasesarxiv-cs-cv

arXiv:2609.32856v1 Announce Type: new Abstract: Vector polygon generation converts visual inputs, e.g., remote sensing (RS) images, into vectorized polygonal geometries, supporting applications such a

Recovering Lower-Dimensional Semialgebraic Support of a Measure from its Moments

arXiv:2609.33420v1 Announce Type: cross Abstract: Recovering probability measures from their moments has numerous applications, esp. in connection with the method of moments in statistics and optimiza

Resource-Aware Federated Mixture-of-Experts with Adaptive Pruning for Onboard Learning in LEO Satellite Constellations

arXiv:2609.31932v1 Announce Type: cross Abstract: Low-Earth-orbit (LEO) satellites are increasingly expected to perform onboard learning for applications such as disaster response and environmental mo

local-aiarxiv-cs-cv

Reuse or Relearn? A Spectral View of Earth Observation Foundation Models

arXiv:2609.32756v1 Announce Type: new Abstract: Foundation models are rarely used as generic, frozen feature extractors; instead, they are fine-tuned for the target downstream application. This practi

Scriboora: Rethinking Human Pose Forecasting

model-releasesarxiv-cs-cv

arXiv:2511.15565v3 Announce Type: replace Abstract: Human pose forecasting predicts future human poses from past observations for applications including action recognition, sports analysis, and human-

SpecRegMatch: Robust Semi-Supervised Regression for Vehicle Interior Noise Prediction

arXiv:2609.34111v1 Announce Type: cross Abstract: The rapid advancement of artificial intelligence has observed increased application in predicting vehicle interior noise levels within the automotive

SR4-Fit: A Unified Interpretable Rule-Based Machine Learning Framework for Informative and Trustworthy Decision-Making

arXiv:2609.34019v1 Announce Type: new Abstract: In many high-stakes applications, machine learning is dominated by black-box models that require post hoc explanations to justify their predictions. The

Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning

arXiv:2609.33715v1 Announce Type: new Abstract: Accurate numerical solutions of partial differential equations (PDEs) are crucial in numerous science and engineering applications. In this work, we int

Towards Eliminating Catastrophic Forgetting in the Curriculum Learning of Math Reasoning Tasks

arXiv:2609.33655v1 Announce Type: new Abstract: Curriculum learning has found broad application across numerous domains. Nevertheless, its effectiveness is intrinsically curtailed by catastrophic forg

Trajectory-Safe Orienteering for Human-Robot Shared Environments

arXiv:2609.34485v1 Announce Type: new Abstract: Orienteering problem (OP) has wide real-world applications and also great potential in human-robot collaboration. However, existing approaches struggle

safetyarxiv-cs-ro

Type-Balanced Federated Learning for Visual Analog Meter Reading

arXiv:2609.31998v1 Announce Type: new Abstract: Analog dial meters are widely deployed in industrial applications and utility sites, where environments and meter types vary and inspection data may be

Video-to-Music Generation for Gameplay Videos

arXiv:2609.31810v1 Announce Type: cross Abstract: Video-to-music models have advanced considerably in the last few years, particularly in film and music video applications. In this paper, we investiga

What masking geometry works best for EEG foundation models?

arXiv:2609.33487v1 Announce Type: new Abstract: EEG foundation models hold promise for scalable brain-signal decoding across clinical and cognitive neuroscience applications, yet their pre-training pi

A Safety-Bounded SDC-to-MCP Gateway for Medical AI Agents

arXiv:2609.31358v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) provides a common interface through which AI applications discover and use external resources and tools. It allows la

safetyarxiv-cs-ai

CacheReforge: Bounded Recovery for Stale KV Caches under Evolving Adapters

arXiv:2609.30884v1 Announce Type: new Abstract: Large language models rely on KV caching to reduce repeated prefill computation in long context and interactive applications. As lightweight adapters ev

How DigitalOcean Manages Credentials for Autonomous Agents

** Built to align with NVIDIA’s Agent Safety Platform strategy for securing autonomous agents When an agent handles confidential material, it needs enough access to do the job and nothing else. The ha

safetydigitalocean

Implicit Neural Representation for Hyperspectral Video Compression

arXiv:2609.31435v1 Announce Type: cross Abstract: With the advent of snapshot cameras, hyperspectral video is becoming more readily available. In recent years, new applications have emerged which have

researcharxiv-cs-ai

Learning Provable Neural Network Observer for Uncertain Dynamical Systems

arXiv:2609.30819v1 Announce Type: new Abstract: In many safety-critical applications, control of uncertain dynamical systems relies on observers that estimate states and external disturbances. Neural

Models Got Talent: Identifying High Performing Wearable Human Activity Recognition Models Without Training

model-releasesarxiv-cs-ai

arXiv:2511.06157v3 Announce Type: replace-cross Abstract: Discovering high performing model architectures for wearables-based Human Activity Recognition (HAR) applications is challenging. The astonish

OmouAI: Argumentative Human-AI Policy Deliberation with Simulated Personas

arXiv:2609.31078v1 Announce Type: new Abstract: Debates amongst agents driven by large language models (LLMs) have demonstrated vast potential in various applications, but when these interactions incl

safetyarxiv-cs-ai

OpenVAM: Open-World Visual Attention Modeling with VLMs

model-releasesarxiv-cs-cv

arXiv:2609.31364v1 Announce Type: new Abstract: Predicting human gaze is a core capability for applications ranging from web/UI design analysis to robotics and human-computer interaction. Yet, most vi

Population loss in shallow ReLU networks: Bias & families of critical points

arXiv:2609.30661v1 Announce Type: new Abstract: The main result presented is a formula for the population loss in the student-teacher kernel model that is applicable to shallow ReLU networks with bias

ScopeBench: Do Agents Preserve Engagement Boundaries Under Goal Pressure?

model-releasesarxiv-cs-ai

arXiv:2609.30325v1 Announce Type: new Abstract: Agents are increasingly deployed with real autonomy in web application and network penetration testing, where a single out-of-scope action can breach a

Skip the Talk, Re-Focus on Vision: Latent Reasoning for Reasoning Segmentation in Multimodal Large Language Models

arXiv:2609.30783v1 Announce Type: cross Abstract: Reasoning segmentation aims to interpret implicit textual queries and enable fine-grained visual perception, which is critical for applications such a

safetyarxiv-cs-ai

I ran a controlled Krea 2 character-training test and wanted to share the results because a few things surprised me.

model-releasesr-stablediffusion

After my last post documenting my LoRA journey, I received a ton of feedback regarding changes to the training process, and decided to do some experimenting. This is using the Fizgig application on a

27 Sept 2026

Tutorials

A Study of the Limits of Collaborative DCT-Based Image Denoising via Interpretable Neural Networks

arXiv:2609.29334v1 Announce Type: new Abstract: Image denoising remains a fundamental problem in image restoration, with applications in photography, biomedical, and scientific imaging. Modern deep ne

tutorialsarxiv-cs-cv

BLADE: Distilled LLM Regularization for Calibrated Knowledge Graph Completion

arXiv:2609.29487v1 Announce Type: new Abstract: Knowledge graph completion models optimize ranking, although many downstream applications require calibrated probabilities. We present BLADE, a variatio

Cross-Modal Emotion Understanding: A Transformer-GAT Approach for Dialogue Emotion Recognition

arXiv:2609.29556v1 Announce Type: new Abstract: Multimodal emotion recognition is a key research area in affective computing, with applications in sentiment analysis, intelligent customer service, and

local-aiarxiv-cs-ai

Agents

DrGait: Biomechanically Grounded Visual Reasoning for Interpretable Clinical Gait Analysis

arXiv:2609.28796v1 Announce Type: cross Abstract: Current automated gait analysis for clinical applications relies on uninterpretable black-box classifiers. Although Vision-Language Models (VLMs) offe

agentsarxiv-cs-ai

Efficient Continuous DEM Reconstruction under Limited Target-Resolution Supervision

arXiv:2609.29864v1 Announce Type: new Abstract: High-resolution digital elevation models (DEMs) support Earth observation applications, but paired training references are often available only at coars

local-aiarxiv-cs-cv

FounRef: Robust, Structure-Preserving, and Fast Metric Refinement of Frozen Monocular Foundation Priors with Sparse Anchors

arXiv:2609.29224v1 Announce Type: new Abstract: Dense metric depth from cameras is essential to real-world 3D applications, yet achieving accuracy, faithful surface geometry, and fast inference simult

local-aiarxiv-cs-cv

Matrix Aggregation Operators

arXiv:2609.28562v1 Announce Type: cross Abstract: Aggregation theory has traditionally focused on operators defined over vectors. However, many applications-including Multi-Criteria Decision Making, G

Safety-oriented pedestrian trajectory prediction at urban intersections using time-to-collision and crossing-zone context

arXiv:2609.29706v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is important for proactive road-safety applications, particularly at urban intersections where pedestrian moti

Sim-to-Real Aware End-to-End Learning Environment for Micromobility

arXiv:2609.28969v1 Announce Type: new Abstract: While end-to-end autonomous driving systems show promise, their application to micromobility vehicles is hindered by simulators failing to capture speci

safetyarxiv-cs-ro

Unraveling the cognitive patterns of Large Language Models through module communities

arXiv:2508.18192v2 Announce Type: replace Abstract: Large Language Models (LLMs) have reshaped our world with significant advancements in science, engineering, and society through applications ranging

researcharxiv-cs-ai