Skip To Main Content
Guoying Lu on Muck Rack

Guoying Lu

As seen in: Wiley Online Library
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Guoying

Contact Guoying, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Trustworthy Legal Reasoning in 2026: A Mid-Year Review of Research, Products, Events, and Governance

|
By Sirui Han, Yidan Huang, Guoying Lu
| preprints.org
You are already at the latest version Legal artificial intelligence is moving beyond answer generation into consequential workflows across legal research, drafting, compliance, litigation support, public legal services, and regulated practice. This shift exposes the limits of conventional evaluation: a plausible answer may still rely on inappropriate authority, outdated law, an inapplicable jurisdiction, or an unreviewable process.
Open in Who Shared Issue with article?

Evaluating the effectiveness of a novel training model in dental preclinical regenerative endodontic education

|
By Jia Hu, Ruonan Chen, Xiuqing Wang, Guoying Lu
| Wiley Online Library Verified
DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request.
Open in Who Shared View Duplicates (89) Issue with article?

Interface Layout Optimization for Electrical Devices Using Heuristic Algorithms and Eye Movement

|
By Tianyu Cheng, Guoying Lu, Jianqin Yu, Junkun Zhou
| ieeexplore.ieee.org
This paper presents a comprehensive evaluation of various YOLO architectures for smoke and wildfire detection, including YOLOv5, YOLOv6, YOLOv7, YOLOv8, and YOLO-NAS. The study aims to assess their effectiveness in early detection of wildfires using the Foggia dataset, comprising 8,974 images specifically designed for this purpose. Performance evaluation employs metrics such as Recall, Precision, F1-score, and mean Average Precision to provide a holistic assessment of the models’ performance.
Open in Who Shared View Duplicates (2) Issue with article?
See all 3 articles