Search: “applications”

arXiv:2609.03427v1 Announce Type: cross Abstract: Path representation learning (PRL) for road networks has received increasing research attention, due to various path-related applications. Existing wo

tutorialsarxiv-cs-ai

4 Sept 2026

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Applications

WireSeg-32K: A Physics-Grounded Synthetic Dataset for Wire Instance Segmentation

DGX agent

arXiv:2609.03102v1 Announce Type: new Abstract: Deformable linear objects such as wires and cables are difficult to segment because they are thin, highly deformable, and frequently self-occluded, whil

applicationsarxiv-cs-cv

4 Sept 2026

A Unified Particle Filter LSTM for Data-Driven Process Simulation

arXiv:2609.01967v1 Announce Type: new Abstract: Data-driven process simulation aims to generate realistic case trajectories from historical event logs without requiring an explicitly specified model o

Access to Astra is rolling out over the coming days. Starting today, enterprise customers in OpenAI's Daybreak Program can get access to Ast…

applicationscognition-ai--x

Access to Astra is rolling out over the coming days. Starting today, enterprise customers in OpenAI's Daybreak Program can get access to Astra. Read more on our blog: https://devin.ai/blog/gpt-6-astra

Addressing Trust in AI Systems through Education: A Didactic Perspective

arXiv:2609.02453v1 Announce Type: cross Abstract: Machine learning (ML) education faces two persistent and connected obstacles: many educational tools present ML as an opaque black box, which leaves l

Bayes-Optimal BER and AUC: Estimation and Evaluation of Estimators

arXiv:2609.02304v1 Announce Type: new Abstract: A fundamental quantity in machine learning is the optimal performance achievable by any model on a given task. Estimating this quantity allows us to dis

Broadcom and Supermicro unify AI factory management

AI factory management is expanding beyond software and servers to encompass the physical systems supporting production workloads. Broadcom Inc. and Super Micro Computer Inc. are integrating their tech

applicationssiliconangle

Door-in-the-Face Requests and Refusal Behaviour in Large Language Models

arXiv:2609.02707v1 Announce Type: new Abstract: Does the door-in-the-face technique work on language models? In humans, a large request that is refused makes a smaller follow-up request more likely to

Equivariant Filter Transformations for Consistent and Efficient Visual--Inertial Navigation

arXiv:2603.24130v2 Announce Type: replace Abstract: This paper presents an equivariant filter (EqF) transformation approach for visual--inertial navigation. By establishing analytical links between Eq

applicationsarxiv-cs-ro

General Demographic Pre-trained Models for Enhancing Predictive Performance Across Diseases and Population

arXiv:2509.07330v3 Announce Type: replace-cross Abstract: Foundation models for healthcare require balancing robust generalization across heterogeneous clinical populations and disease settings with t

Generating Medical Image Counterfactuals using Causal Explanations

arXiv:2609.02697v1 Announce Type: new Abstract: Deep learning models have achieved impressive performance in medical image diagnosis, yet their deployment in clinical settings remains constrained by l

GPT-6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, …

GPT-6 Astra is rolling out today to a limited set of organizations and over the coming days will become available to all ChatGPT Plus, Pro, Business, and Enterprise users, as well as through the OpenA

applicationsopenai--x

Introducing WeatherNext 3️⃣— our most advanced global weather AI model yet from @GoogleDeepmind and @GoogleResearch With prediction capabili…

Introducing WeatherNext 3️⃣— our most advanced global weather AI model yet from @GoogleDeepmind and @GoogleResearch With prediction capabilities that are up to 5x sharper than WeatherNext 2, the model

applicationsgoogle-ai--x

I've watched a lot of good tools die in production. Not because they didn't work. Because the two people who understood them rolled off the …

I've watched a lot of good tools die in production. Not because they didn't work. Because the two people who understood them rolled off the show, and what was left was a graph nobody could read. So th

applicationscomfyui--x

Learning to Attract and Repel: Dual Quality Margin Learning for Face Recognition (DQM-Face)

arXiv:2609.02644v1 Announce Type: new Abstract: Face recognition in unconstrained environments remains highly challenging due to diverse and extreme variations encountered in real-world scenarios. To

LoFi RADIO: A Distilled In-Domain Backbone Applied for Artifact-Severity Grading of Ultra-Low-Field Neonatal Brain MR

arXiv:2609.02676v1 Announce Type: cross Abstract: Ultra-low-field MRI makes neonatal brain imaging deploy- able in low-resource settings, but its low SNR, lack of shielding, and long scan duration mak

MAOL: Morphology-Aware Ordinal Learning for Fine-Grained Industrial Defect Severity Grading

arXiv:2609.02266v1 Announce Type: new Abstract: Fine-grained defect severity grading is essential for industrial inspection, yet remains challenging due to the ordinal nature of severity labels, the s

Marginal Expected Revenue for Jointly Ranking Auction and Fixed-Price Listings in E-Commerce Sponsored Search

arXiv:2609.01628v1 Announce Type: cross Abstract: E-commerce search ranking must balance multiple objectives--relevance, user engagement, and platform revenue--when allocating impression slots to comp

MISApp: Multi-Hop Intent-Aware Session Graph Learning for Next App Prediction

arXiv:2603.21653v2 Announce Type: replace Abstract: Predicting the next mobile app a user will launch is essential for proactive mobile services. Yet accurate prediction remains challenging in real-wo

Network-Aware Forecasting on Wireless Access Points

arXiv:2609.01957v1 Announce Type: cross Abstract: Enterprise wireless access points (APs) are promising platforms for predictive machine learning (ML), but their primary responsibility remains providi

RGB-to-IR image translation for infrared vehicle detection in unseen UAV domains

arXiv:2609.02556v1 Announce Type: new Abstract: Synthetic training data is crucial for developing vision AI when real-world data is scarce, as in thermal infrared (IR) aerial vehicle detection. While

RINSE: Robust Target-Time Normality Estimation for Zero-Shot Graph Anomaly Detection

arXiv:2609.02497v1 Announce Type: cross Abstract: Zero-shot graph anomaly detection seeks to deploy a detector trained on source graphs to unseen, unlabeled targets, yet domain shift can make source-d

Robust Streaming PCA

arXiv:1902.03223v4 Announce Type: replace-cross Abstract: We consider streaming principal component analysis when the stochastic data generating model is subject to perturbations. While existing model

SCULPT: Training Edge Vision Models for Post-Training Quantization Readiness

arXiv:2609.01743v1 Announce Type: new Abstract: Edge vision models are difficult to deploy on resource-constrained hardware, making low-bit post-training quantization (PTQ) attractive. In practice, st

Model Releases

SCX Router: Streaming Zero-Shot Model Selection with a Decoder-KV Classifier and a Real-World Task Ontology

model-releasesarxiv-cs-ai

arXiv:2609.02292v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) and the growing diversity of their applications presents a unique optimization opportunity: sele

Set up OpenAI ChatGPT Codex with LiteLLM on Amazon ECS and Amazon Bedrock

Deploy a customer-operated LiteLLM gateway on Amazon ECS with AWS Fargate, connect it to an OpenAI model on Amazon Bedrock, and configure Codex to route requests through the gateway's Responses API wi

applicationsaws-ml-blog

Sources: Saudi AI company Humain is planning to raise an initial $2.5B fund to help finance data center capacity of 250 MW in Saudi Arabia (Omar El Chmouri/Bloomberg)

Omar El Chmouri / Bloomberg: Sources: Saudi AI company Humain is planning to raise an initial 2.5B fund to help finance data center capacity of 250 MW in Saudi Arabia — Artificial intelligence firm Hu

applicationstechmeme

Model Releases

SpeakPay: Domain-Adaptive LoRA Fine-Tuning of Whisper for Low-Resource Nepali Financial Speech Recognition

model-releasesarxiv-cs-cl

arXiv:2609.01737v1 Announce Type: new Abstract: Mobile payment applications in Nepal are graphically mediated and largely inaccessible to visually impaired users. This paper presents SpeakPay, a voice

The AI model is table stakes: Enterprise data is where the battle begins

Enterprises need practical solutions when it comes to artificial intelligence implementation. As organizations look to move AI projects from proof of concept into production, navigating the challenges

applicationssiliconangle

The LA Unified School District bars ~378,000 students from using AI tools on district-provided laptops and tablets as officials review AI's role in classrooms (Julia Szymanski/LAmag)

Julia Szymanski / LAmag: The LA Unified School District bars ~378,000 students from using AI tools on district-provided laptops and tablets as officials review AI's role in classrooms — The district h

applicationstechmeme

UnCapsTSR: An Unsupervised Transformer-based Image Super-Resolution Approach for Capsule Endoscopy Images

arXiv:2609.02476v1 Announce Type: new Abstract: Wireless Capsule Endoscopy (WCE) captures and streams video while passing through a patient's Gastrointestinal (GI) tract and is used to examine its irr

Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: A Comparative Study

arXiv:2507.08468v2 Announce Type: replace Abstract: This paper provides an experimental evaluation of the capability of large language models (LLMs) to assist in legal decision-making within the frame

applicationsarxiv-cs-cl

WildFab: Multi-Axis 3D Printing from Models in the Wild

arXiv:2609.02413v1 Announce Type: cross Abstract: Multi-axis 3D printing enables support-free fabrication and improved part quality, but robustly processing real-world geometries remains challenging.

applicationsarxiv-cs-ro

Wound3DAssist: A Practical Framework for 3D Wound Assessment

arXiv:2508.17635v2 Announce Type: replace Abstract: Managing chronic wounds remains a major healthcare challenge, with clinical assessment often relying on subjective and time-consuming manual documen

A Machine Learning-Driven Solution for Denoising Inertial Confinement Fusion Images

arXiv:2511.16717v3 Announce Type: replace-cross Abstract: Neutron imaging is essential for diagnosing and optimizing inertial confinement fusion implosions at the National Ignition Facility. Due to th

A Mathematical Framework for Legacy, Governance, and Decision Integrity in Enterprise AI

arXiv:2609.00572v1 Announce Type: cross Abstract: Enterprise artificial intelligence is increasingly embedded in decisions that must remain lawful, explainable, adaptable, and accountable despite pers

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

arXiv:2609.01601v1 Announce Type: cross Abstract: The repository-level code generation task requires synthesizing code that satisfies task requirements while remaining consistent with the target repos

AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generation

arXiv:2609.00818v1 Announce Type: new Abstract: We argue that financial report generation should operate at the analytical rather than structural level, composing content from data-derived insights ra

Anamnesis: An Open-Source Platform for Large-Scale Backstory-Conditioned Survey Simulation

arXiv:2607.10628v2 Announce Type: replace-cross Abstract: We present Anamnesis, an interactive system for demographically controllable survey simulation using large language models. Open-source and de

Autoresearch for Marketplace Catalogs: From Legacy Forms to AI-Native Matching

arXiv:2609.00274v1 Announce Type: new Abstract: Two-sided service marketplaces are moving from deterministic request-form intake to AI-native probabilistic matching, enabled by large language models (

Cleaner Speech, Weaker Generalization: Revisiting Pitt-Derived Benchmarks for Alzheimer's Disease Detection

arXiv:2609.00276v1 Announce Type: cross Abstract: Speech-based Alzheimer's disease (AD) detection increasingly relies on speech-enhanced and curated versions of the Pitt Corpus, where speech enhanceme

Confess What You Know: Forget-Set Misalignment with Model Knowledge in LLM Unlearning

arXiv:2609.00605v1 Announce Type: cross Abstract: Machine unlearning for large language models (LLMs) often assumes that a pre-defined forget set matches what the model has memorized, but this frequen

Safety

Context-Aware Intelligent Vehicles

arXiv:2609.00682v1 Announce Type: new Abstract: Intelligent vehicles increasingly support adaptive applications beyond driving themselves, ranging from context-aware ADAS and automated driving to in-c

safetyarxiv-cs-ro

CoVer: Conflict-Aware Claim Verification

arXiv:2609.00508v1 Announce Type: new Abstract: Social media fact-checking has long been challenged by evidence-level and aggregation-level conflicts, where erroneous evidence mimics authoritative new

Degradation-based augmented training for robust individual animal re-identification

arXiv:2603.04163v2 Announce Type: replace Abstract: Wildlife re-identification aims to recognise individual animals by matching query images to a database of previously identified individuals, based o

Research

Design and Implementation of a Kalman Filter-Infused Algorithm for Tilt Estimation

arXiv:2609.00730v1 Announce Type: new Abstract: Accurate tilt angle estimation is important in many engineering applications, such as robotics, motion tracking, and embedded control systems. However,

researcharxiv-cs-cv

Model Releases

Efficient and Robust Absolute Pose Estimation via Gravity-Prior-Driven Transformation Decoupling and Pose Refinement

model-releasesarxiv-cs-cv

arXiv:2609.00713v1 Announce Type: new Abstract: Estimation of the absolute pose of an object is an essential task for various robotic applications. Recently, incorporating gravity direction as prior i

Efficiently Estimating Optimal Hyperparameter Scaling Laws through Power-Law Entropy Search

arXiv:2609.01431v1 Announce Type: cross Abstract: Optimal hyperparameter scaling laws describe how the best hyperparameters for large language model (LLM) training change with model and data scale, en