Search: “applications”

Alliance Beats Isolation: Unifying Heterogeneous Allied Datasets Improves Classifier Performance

arXiv:2609.19748v1 Announce Type: new Abstract: In many application domains, such as student dropout, insurance fraud, loan approval, and machine failures, several labelled public datasets are availab

researcharxiv-cs-lg

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Research

Bayesian Continuum Robot Dynamics and State Estimation

DGX agent

arXiv:2609.20605v1 Announce Type: new Abstract: Recent factor graph approaches to continuum robot state estimation have been successful for quasi-static applications and spatiotemporal estimation usin

researcharxiv-cs-ro

18 Sept 2026

Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia

model-releasesarxiv-cs-cl

arXiv:2509.09121v2 Announce Type: replace Abstract: Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specif

CORAL-AUV: CFD Oriented Reinforcement Learning for Autonomous Underwater Vehicles

arXiv:2607.09557v2 Announce Type: replace Abstract: Fine grain control and positioning of autonomous underwater vehicles (AUVs) is critical for sampling, maintenance, and survey applications. Traditio

safetyarxiv-cs-ro

Elastic Spectral State Space Models for Train-Once Budgeted Inference

arXiv:2601.22488v3 Announce Type: replace Abstract: Modern sequence models are typically trained at a fixed computational capacity, while real-world applications require deployment across platforms wi

Graph-Based Design of Soft Grippers with Multi-Objective Quality-Diversity Optimisation

arXiv:2609.20087v1 Announce Type: new Abstract: Effective manipulation across diverse objects is critical for applications ranging from agricultural harvesting to laboratory and domestic automation. W

researcharxiv-cs-ro

Agents

HEROIC: Heterogeneous Evidential Reasoning for Open-Vocabulary Identification and Cross-Robot Collaboration

arXiv:2609.19803v1 Announce Type: new Abstract: Multi-agent heterogeneous air-ground robot teams are attractive for open world search, with applications for reconnaissance, urban search and rescue mis

agentsarxiv-cs-ro

Learning Slope-Adaptive Whole-Body Locomotion for Humanoid Robots in Roofing Construction

arXiv:2609.20558v1 Announce Type: new Abstract: Roofing requires workers to coordinate locomotion, balance, and work-related body motions on pitched surfaces, creating a challenging application for hu

safetyarxiv-cs-ro

Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning

arXiv:2609.20389v1 Announce Type: cross Abstract: Offline policy evaluation (OPE) is crucial in high-stakes reinforcement learning applications, where new policies must be assessed reliably before dep

Perturbing the Phase: Analyzing Adversarial Robustness of Complex-Valued Neural Networks

arXiv:2602.06577v2 Announce Type: replace-cross Abstract: Complex-valued neural networks (CVNNs) are rising in popularity for all kinds of applications. To safely use CVNNs in practice, analyzing thei

QUALS: Corpus Equilibrium for Universal Forecasting via Pattern Quantization and Learnability Synchronization

arXiv:2609.20156v1 Announce Type: cross Abstract: Ubiquitous time series data across diverse domains enables critical applications in areas such as transportation systems and power grids. Recently, tr

Hardware

S4R: Scaling for Rigid-Body Interpenetration Resolution

arXiv:2609.20524v1 Announce Type: cross Abstract: Rigid-body interpenetration frequently occurs in procedurally assembled and generated scenes and must be removed before downstream applications such a

hardwarearxiv-cs-ro

SETTer: Sparse-Encoder Transformer for Long-term Multivariate Time Series Forecasting

arXiv:2609.20086v1 Announce Type: new Abstract: Long-term multivariate time series plays a significant role in many application areas such as power systems, trading, etc. However, their accurate predi

ZeroHAT: Behavior-Conditioned Zero-Shot Human Activity Trace Generation

arXiv:2609.20310v1 Announce Type: new Abstract: Human activity traces record individuals' timestamped visits to points of interest and are essential for applications such as mobility prediction and ur

A Non-Linear Neuron Based Detection of Isolated Pixels in Binary and Grayscale Images using Contrast Sensitive Receptive Fields

arXiv:2609.18399v1 Announce Type: cross Abstract: Identifying isolated points is important in image processing applications such as medical imaging, astronomy and quality control management. Other dom

Beyond Direct Sensing: Harnessing Indirect Observations from Third-Party Sensors in Vehicle Tracking

arXiv:2609.18173v1 Announce Type: cross Abstract: Vehicle tracking is fundamental to applications ranging from urban mobility and public safety to security and defense. Conventional tracking relies on

Bias Amplification in Multi-Agent Network: How Biased Agents Shape Opinions and Rhetoric

arXiv:2609.18306v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in applications involving interaction between agents, where their output plays a role in collecti

FairLRF: Achieving Fairness through Sparse Low Rank Factorization

arXiv:2511.16549v2 Announce Type: replace Abstract: As deep learning (DL) techniques become integral to various applications, ensuring model fairness while maintaining high performance has become incr

Fetch My Beer: Synthetic-to-real Hierarchical Policy for Smooth Pick-and-place

arXiv:2609.18119v1 Announce Type: new Abstract: Many real-world robotic applications require dynamically sensitive manipulation, where success depends not only on reaching a target state but on mainta

safetyarxiv-cs-ro

Large Language Models Versus Physicians in Traditional Chinese Medicine: A Real-World Clinical Case Evaluation

arXiv:2609.17544v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical applications, yet their assessment for real-world traditional Chinese medicine

safetyarxiv-cs-cl

LightSleepX: A Lightweight, Inception-Based Dual-Modal Network for Sleep Staging

arXiv:2609.19062v1 Announce Type: new Abstract: Automatic sleep staging is fundamental to personal health monitoring, yet many existing approaches are ill-suited for real-world applications. Tradition

Prosthesis-Aware 3D Human Pose Estimation: A Dataset and Benchmark for RSP Users

model-releasesarxiv-cs-cv

arXiv:2609.18406v1 Announce Type: new Abstract: Recovering 3D human body motion from video is important for applications such as rehabilitation assessment and sports performance evaluation. For prosth

Local Ai

TalkMatrix: Generating Character Dialogue that is Both Consistent and Diverse

arXiv:2609.19022v1 Announce Type: cross Abstract: Candidate-based decoding typically selects a completion for each prompt independently, but many applications require a collection of outputs that sati

local-aiarxiv-cs-ai

Tutorials

EventEgoHands++: Event-based Egocentric 3D Hand Mesh Reconstruction with Real Dataset

arXiv:2609.17189v1 Announce Type: new Abstract: 3D hand mesh reconstruction is a challenging yet essential task for downstream applications, including human-robot interaction and AR/VR. Although conve

tutorialsarxiv-cs-cv

FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection

arXiv:2609.16842v1 Announce Type: new Abstract: Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD

researcharxiv-cs-cv

Federated stochastic bilevel optimization with fully first-order gradients

arXiv:2609.16350v1 Announce Type: new Abstract: Federated stochastic bilevel optimization has been actively studied in recent years due to its widespread applications in machine learning. However, mos

researcharxiv-cs-lg

Nonsmooth Optimization via Orthogonalized Momentum

arXiv:2609.13677v1 Announce Type: cross Abstract: Modern real application problems involve matrix-valued parameters, yet conventional optimizers treat them as vectors, thereby motivating matrix-aware

Observational Multiplicity

arXiv:2507.23136v2 Announce Type: replace Abstract: Many prediction tasks can admit multiple models that can perform almost equally well. This phenomenon can undermine interpretability and safety when

PanoGS-SLAM: Panoramic 3D Gaussian Splatting SLAM

arXiv:2609.17387v1 Announce Type: new Abstract: Real-time dense SLAM is a core capability for robotics applications that require robust localization and high- quality mapping in dynamic or fast-changi

researcharxiv-cs-cv

Scalable Algorithms for Approximate DNF Model Counting

arXiv:2601.10511v2 Announce Type: replace-cross Abstract: Model counting of Disjunctive Normal Form (DNF) formulas is a critical problem in applications such as probabilistic inference and network rel

SlotDiT: Object-Centric Representations for Diffusion Transformers

arXiv:2609.17414v1 Announce Type: new Abstract: Text-conditioned latent diffusion models perform strongly in video generation and are promising backbones for robotic applications. However, existing ap

safetyarxiv-cs-cv

Active Learning with Bayesian Multi-Fidelity Laplace Neural Operators for Oscillatory Parametric PDEs

arXiv:2502.00550v2 Announce Type: replace Abstract: Surrogate models of parametric dynamical systems are essential for many-query and real-time predictions in engineering applications such as design o

researcharxiv-cs-lg

Admissable: Training Reinforcement Learning Agents against Adversarial Missingness

arXiv:2609.15297v1 Announce Type: new Abstract: In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. I

Bangla Sentence Function Classification: Corpus Development, Model Benchmarking, and Interpretability

model-releasesarxiv-cs-ai

arXiv:2609.13869v1 Announce Type: cross Abstract: Automatic sentence function identification is important for many downstream natural language processing (NLP) applications such as dialogue systems, t

Can We Trust the Judges? Validation of Factuality Evaluation Methods via Answer Perturbation

arXiv:2609.15561v1 Announce Type: new Abstract: Evaluating the factual correctness of large language models (LLMs) is vital for many applications. But are our evaluation tools themselves trustworthy?

researcharxiv-cs-cl

Agents

Data Security in Large Language Models: Risks, Defense, and Directions

arXiv:2508.02312v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine t

agentsarxiv-cs-ai

From Words to Wavelengths: VLMs for Few-Shot Multispectral Object Detection

arXiv:2512.15971v2 Announce Type: replace Abstract: Multispectral object detection is critical for safety-sensitive applications such as autonomous driving and surveillance, where robust perception un

safetyarxiv-cs-cv

Hardware

Goal-Oriented Communications for Physical AI: Design and Testbed

arXiv:2609.15895v1 Announce Type: new Abstract: Physical AI relies on frequently-updated, latency-sensitive video stream to perceive, reason, and interact with the physical world, resulting in strict

hardwarearxiv-cs-ro

Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification

arXiv:2609.15145v1 Announce Type: new Abstract: The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning ca

researcharxiv-cs-cl

Isolation-based Spherical Ensemble Representations for Tabular Anomaly Detection

arXiv:2510.13311v2 Announce Type: replace Abstract: Unsupervised tabular anomaly detection is a critical task with applications spanning offensive language detection, network security, and quality con

Agents

Multilingual Agent System for Inclusive Wildfire Evacuation Guidance

arXiv:2609.03301v1 Announce Type: cross Abstract: Wildfire seasons have become 84 days longer in the current days than in the 1970s, causing enormous threats to one's financial status and short- and l

agentsarxiv-cs-ai

Natural Language Knowledge Graph Query Execution: Leveraging Controlled Semantics in the LLM Context Window

model-releasesarxiv-cs-ai

arXiv:2609.14652v1 Announce Type: cross Abstract: Large Language Model (LLM) applications often transfer domain concepts into the model's context informally, through prompt prose, schema dumps, and ex

Local Ai

Noise-Aware and Dynamically Adaptive Federated Defense Framework for SAR Image Target Recognition

arXiv:2601.00900v2 Announce Type: replace-cross Abstract: As a critical application of computational intelligence in remote sensing, deep learning-based synthetic aperture radar (SAR) image target rec

local-aiarxiv-cs-cv

Physics Informed Neural Network model for the dynamical study of Abdominal Aortic Aneurysm

arXiv:2609.15104v1 Announce Type: cross Abstract: We present the development and application of a three-dimensional Physics-Informed Neural Network (PINN) framework for the investigation of haemodynam

PolicyMem: Geometric Policy Memory for LLM Governance

arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing

safetyarxiv-cs-ai

Tutorials

Representing Clinical Conditions on Vital Signs from Healthy Individuals using Latent Modeling

arXiv:2609.15379v1 Announce Type: new Abstract: Machine learning can be crucial to help scale complex signal processing applications in scenarios such as healthcare. However, these machine learning mo

tutorialsarxiv-cs-lg

Safe Meta-Reinforcement Learning via Information Space Reachability

arXiv:2609.15915v1 Announce Type: new Abstract: Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL i

SAR-FAH: A Frequency-Adaptive Hybrid Network based on Neural ODEs for Structural-Preserving SAR Despeckling

arXiv:2511.05890v2 Announce Type: replace Abstract: Synthetic Aperture Radar (SAR) images are inherently degraded by speckle noise that severely limits their reliability in high-precision applications

researcharxiv-cs-cv