Weixin Liang

1.6k total citations · 1 hit paper
20 papers, 779 citations indexed

About

Weixin Liang is a scholar working on Artificial Intelligence, Health Informatics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Weixin Liang has authored 20 papers receiving a total of 779 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 5 papers in Health Informatics and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Weixin Liang's work include Topic Modeling (7 papers), Artificial Intelligence in Healthcare and Education (5 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Weixin Liang is often cited by papers focused on Topic Modeling (7 papers), Artificial Intelligence in Healthcare and Education (5 papers) and Explainable Artificial Intelligence (XAI) (3 papers). Weixin Liang collaborates with scholars based in United States, China and Switzerland. Weixin Liang's co-authors include James Zou, Eric Q. Wu, Li Fei-Fei, Ce Zhang, Matei Zaharia, Girmaw Abebe Tadesse, Daniel E. Ho, Mert Yüksekgönül, Yining Mao and Yu Zhou and has published in prestigious journals such as International Journal of Computer Vision, Physics in Medicine and Biology and Nature Human Behaviour.

In The Last Decade

Weixin Liang

20 papers receiving 741 citations

Hit Papers

Advances, challenges and opportunities in creating data f... 2022 2026 2023 2024 2022 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Advances, challenges and opportunities in creating data for trustworthy AI
    2022 283 citations Weixin Liang, Girmaw Abebe Tadesse et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Weixin Liang United States 10 355 197 89 64 63 20 779
Tianyu Wu China 5 347 1.0× 242 1.2× 47 0.5× 79 1.2× 61 1.0× 8 820
Emily Reif United States 10 456 1.3× 91 0.5× 110 1.2× 26 0.4× 72 1.1× 17 802
Rita Frieske Hong Kong 2 885 2.5× 291 1.5× 114 1.3× 117 1.8× 106 1.7× 3 1.5k
Daniel Smilkov North Macedonia 6 253 0.7× 69 0.4× 145 1.6× 30 0.5× 52 0.8× 10 533
Kaijie Zhu China 3 552 1.6× 89 0.5× 87 1.0× 30 0.5× 28 0.4× 4 1.1k
Franck Dernoncourt United States 20 951 2.7× 225 1.1× 183 2.1× 99 1.5× 41 0.7× 102 1.4k
Xiaoyuan Yi China 3 538 1.5× 86 0.4× 81 0.9× 29 0.5× 25 0.4× 6 1.0k
Eduardo Mosqueira-Rey Spain 11 238 0.7× 61 0.3× 58 0.7× 27 0.4× 36 0.6× 31 669

Countries citing papers authored by Weixin Liang

Since Specialization
Citations

This map shows the geographic impact of Weixin Liang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Weixin Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weixin Liang more than expected).

Fields of papers citing papers by Weixin Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weixin Liang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Weixin Liang. The network helps show where Weixin Liang may publish in the future.

Co-authorship network of co-authors of Weixin Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Weixin Liang. A scholar is included among the top collaborators of Weixin Liang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weixin Liang. Weixin Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Yizheng, Weixin Liang, Mark K. Buyyounouski, et al.. (2025). Automated radiotherapy treatment planning guided by GPT-4Vision. Physics in Medicine and Biology. 70(15). 155002–155002. 4 indexed citations
2.
Liang, Weixin, Zhengxuan Wu, Hancheng Cao, et al.. (2025). Quantifying large language model usage in scientific papers. Nature Human Behaviour. 9(12). 2599–2609. 8 indexed citations
3.
Liang, Weixin, Hancheng Cao, Daisy Yi Ding, et al.. (2024). Can Large Language Models Provide Useful Feedback on Research Papers? A Large-Scale Empirical Analysis. NEJM AI. 1(8). 70 indexed citations
4.
Liang, Weixin, et al.. (2024). Systematic analysis of 32,111 AI model cards characterizes documentation practice in AI. Nature Machine Intelligence. 6(7). 744–753. 2 indexed citations
5.
Hu, Congxue, Jing Chen, Weixin Liang, et al.. (2024). Dissecting the cellular reprogramming and tumor microenvironment in left- and right-sided Colorectal Cancer by single cell RNA sequencing. Translational research. 276. 22–37. 1 indexed citations
6.
Liang, Weixin, Mert Yüksekgönül, Yining Mao, Eric Q. Wu, & James Zou. (2023). GPT detectors are biased against non-native English writers. Patterns. 4(7). 100779–100779. 186 indexed citations
7.
Liang, Weixin, Kyle Mahowald, Jennifer L Raymond, et al.. (2023). How random is the review outcome? A systematic study of the impact of external factors on eLife peer review. bioRxiv (Cold Spring Harbor Laboratory). 1 indexed citations
8.
Wu, Kevin, Eric Q. Wu, Weixin Liang, et al.. (2023). Characterizing the Clinical Adoption of Medical AI Devices through U.S. Insurance Claims. NEJM AI. 1(1). 46 indexed citations
9.
Liang, Weixin, Scott Elrod, Daniel A. McFarland, & James Zou. (2022). Systematic analysis of 50 years of Stanford University technology transfer and commercialization. Patterns. 3(9). 100584–100584. 7 indexed citations
10.
Liang, Weixin, Girmaw Abebe Tadesse, Li Fei-Fei, et al.. (2022). Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nature Machine Intelligence. 4(10). 904–904. 5 indexed citations
11.
Liang, Weixin, Girmaw Abebe Tadesse, Daniel E. Ho, et al.. (2022). Advances, challenges and opportunities in creating data for trustworthy AI. Nature Machine Intelligence. 4(8). 669–677. 283 indexed citations breakdown →
12.
Liang, Weixin, et al.. (2021). GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering. 79–86. 24 indexed citations
13.
Liang, Weixin & James Zou. (2021). Neural Group Testing to Accelerate Deep Learning. 958–963. 6 indexed citations
14.
15.
Liang, Weixin, James Zou, & Yu Zhou. (2020). ALICE: Active Learning with Contrastive Natural Language Explanations. 4380–4391. 19 indexed citations
16.
Liang, Weixin, James Zou, & Yu Zhou. (2020). Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. 1363–1374. 9 indexed citations
17.
Liang, Weixin, et al.. (2020). MOSS: End-to-End Dialog System Framework with Modular Supervision. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 8327–8335. 32 indexed citations
18.
Liang, Weixin, Ziyan Feng, Youjie Li, et al.. (2019). DeepStore. 224–238. 46 indexed citations
19.
Feng, Zunlei, et al.. (2019). CU-Net: Component Unmixing Network for Textile Fiber Identification. International Journal of Computer Vision. 127(10). 1443–1454. 16 indexed citations
20.
Liang, Weixin, et al.. (2018). MemCloak. 187–197. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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