Search: “applications”

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

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Research

Federated stochastic bilevel optimization with fully first-order gradients

DGX agent

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

16 Sept 2026

Nonsmooth Optimization via Orthogonalized Momentum

model-releasesarxiv-cs-lg

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

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

researcharxiv-cs-ai

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

model-releasesarxiv-cs-lg

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

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

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

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

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

researcharxiv-cs-ai

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

StackHawk’s Wingman fixes security flaws while the AI agent is still coding

model-releasessiliconangle

Application security company StackHawk Inc. today launched Wingman, a tool that fixes security vulnerabilities inside the artificial intelligence coding session that produced the flawed code. The soft

To do(x) or not to do(x): Medical Image Counterfactuals for Dataset Augmentation

arXiv:2609.14124v1 Announce Type: cross Abstract: Medical image analysis is often hindered by biased datasets, which can lead to biased models and limited clinical applicability. A promising strategy

safetyarxiv-cs-ai

Zero-shot video highlight detection based on text descriptions and synthetic images

arXiv:2609.14790v1 Announce Type: new Abstract: Detecting video highlights, the most informative or engaging moments in a video, is important for applications such as video summarization and content r

DCRA: Diffusion-Conditioned Representation Alignment for Robust Time-Series Learning

arXiv:2609.11997v1 Announce Type: new Abstract: Learning robust representations for time-series signals under noise and distribution shifts remains challenging, especially in clinical applications suc

Distributed Stochastic Optimal Control for Pattern-Oriented Swarms

arXiv:2609.12959v1 Announce Type: new Abstract: While offering significant promise for diverse applications, pattern-oriented swarms encounter multifaceted challenges in geometric control, self-organi

safetyarxiv-cs-ro

From Bench-to-Bedside: A Review of Clinical Trials in Drug Discovery and Development

arXiv:2412.09378v4 Announce Type: replace-cross Abstract: Clinical trials bridge basic research and clinical application, serving as essential steps in drug development. This review examines clinical

safetyarxiv-cs-cl

Guided Adversarial Robust Transfer Learning with Source Mixing

arXiv:2309.06534v2 Announce Type: replace Abstract: Transfer learning is a critical technique that enables the application of knowledge gained from existing tasks or domains to improve performance on

researcharxiv-cs-lg

Intelligence is yours. Let's keep it that way.

model-releasesdigitalocean

Intelligence was yours. A founder’s intellectual property, business logic, differentiation, their intelligence, was once theirs alone. You built it, you owned it, and no tools/platform vendor stood be

Hardware

Nvidia expands CUDA-Q platform to support fault-tolerant quantum processors

Nvidia Corp. said today it’s tackling one of the major headaches for developers of quantum applications with the launch of a new orchestration layer within its open-source CUDA-Q platform. The announc

hardwaresiliconangle

Tuning ROS 2 for Energy-Efficient Navigation: Empirical Insights from Costmap 2D Configurations

arXiv:2609.12971v1 Announce Type: new Abstract: Robots are increasingly used in diverse application areas, where autonomous navigation plays a central role. As these systems become more widespread, im

agentsarxiv-cs-ro

UniMo: Unifying Human and Animal Motion Generation

arXiv:2609.12342v1 Announce Type: new Abstract: The conditional generation of 3D motion has emerged as a key research topic due to its wide applicability across robotics, AR/VR, gaming, and content cr

Style transfer capabilities of different open-source methods 2026 Update

model-releasesr-stablediffusion

Style transfer capabilities of different open-source methods 2026 Update This is the updated version of the study published at 2025.09.12. Link: https://www.reddit.com/r/StableDiffusion/comments/1nfoz

13 Sept 2026

A-JIT: Agentic Just-In-Time Software Construction

arXiv:2609.10248v1 Announce Type: cross Abstract: Traditional software delivery assumes a static paradigm: code is constructed prior to execution and deployed as a fixed artifact. We present Agentic J

A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Model

arXiv:2408.02920v2 Announce Type: replace-cross Abstract: The rapid advancement of AI technology has led to widespread applications of agent systems across various domains. However, the need for detai

Alignment Reduces Expressed but Not Encoded Gender Bias: A Unified Framework and Study

arXiv:2603.24125v3 Announce Type: replace Abstract: During training, Large Language Models (LLMs) learn social regularities that can lead to gender bias in downstream applications. Most mitigation eff

safetyarxiv-cs-cl

Byzantine-Robust Federated Fire Detection with a Rotating Coordinator

arXiv:2609.10647v1 Announce Type: new Abstract: We study the application of federated learning (FL) to indoor fire detection. Such fire-detection systems use edge cameras that record sensitive footage

researcharxiv-cs-lg

Local Ai

ChatGPT Desktop (the Codex app) can now be configured to use Ollama models. Download or update to Ollama 0.34 to get started.

ChatGPT Desktop (the Codex app) now supports integration with Ollama models, allowing users to run local LLMs within the application. To utilize this feature, simply download or upgrade to Ollama vers

local-aiollama--x

Do Agents Know When They Succeed? Calibrating Agent Confidence from Internal Representations

arXiv:2609.09448v1 Announce Type: new Abstract: As agentic systems getting adopted rapidly in safety critical applications, it is vital to measure the confidence associated with the agentic actions. I

safetyarxiv-cs-ai

Freehand Sketching for End-User Programming of Robot Swarms

arXiv:2609.11078v1 Announce Type: new Abstract: Robot swarms are increasingly used in applications where accessible interaction with non-expert users is desirable. This paper investigates freehand ske

agentsarxiv-cs-ro

REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving

arXiv:2609.11209v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive large language model (LLM) applications by conditioning generation on retrieved docu

researcharxiv-cs-cl

Risk-Averse Decision Making with Multi-Level Reliability Guarantees

arXiv:2609.11524v1 Announce Type: cross Abstract: Many applications in engineering, including wireless broadcasting, require designs that provide performance certificates at different target outage le

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

10 Sept 2026

AgentFairBench: Do LLM Agents Discriminate When They Act?

model-releasesarxiv-cs-ai

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

10 Sept 2026

Industry

Amazon Quick is now generally available on desktop