Wei‐Yao Wang

74 papers receiving 1.5k citations

Wei‐Yao Wang's Hit Papers

LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters 2025 · 34 citations
340+2+4Years since publication100200300

Peers

Wei‐Yao Wang
Comparison fields: 5 of 148
  • Molecular Medicine 134
  • Cancer Research 242
  • Computer Vision and Pattern Recognition 330
  • Signal Processing 117
  • Infectious Diseases 168
Replace Yingwei Chen with:
Yingwei Chen China
Qiang Huang China
Dongxin Liu China
Jianwei Lu China
Yizhen Zhang United States
Yushan Chen China
Kwang‐Hyun Park South Korea
Chung‐Chih Lin Taiwan
Hongyan Wang China
Scott Ferguson United States
Wei‐Yao Wang relative to Yingwei Chen China Yingwei Chen's profile →
Citations per field
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Yingwei Chen · 1×
Citations per year

Countries citing papers authored by Wei‐Yao Wang

Since Specialization
Citations

This map shows the geographic impact of Wei‐Yao Wang'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 Wei‐Yao Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei‐Yao Wang more than expected).

Fields of papers citing papers by Wei‐Yao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei‐Yao Wang. 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 Wei‐Yao Wang. The network helps show where Wei‐Yao Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Wei‐Yao Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Wei‐Yao Wang Line = papers co-authored together Wei‐Yao Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1
What Makes Training Multi-Modal Classification Networks Hard?
Hit paper breakdown →
2020312
2 201878
3 201276
4 201268
5 201865
6 202162
7 201659
8 201957
9 202056
10 202342
11 201039
12 201838
13 202137
14 202335
15
LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters
Hit paper breakdown →
202534
16 201928
17 200926
18 201125
19 201725
20 202224

About Wei‐Yao Wang

Wei‐Yao Wang is a scholar working on Artificial Intelligence, Molecular Biology, Computer Vision and Pattern Recognition, Infectious Diseases and Economics and Econometrics, having authored 80 papers that have together received 1.6k indexed citations. Recurring topics across this work include Sports Analytics and Performance (8 papers), Anomaly Detection Techniques and Applications (7 papers), Antimicrobial Resistance in Staphylococcus (7 papers), Time Series Analysis and Forecasting (6 papers), Human Pose and Action Recognition (5 papers), Antibiotic Resistance in Bacteria (4 papers), Topic Modeling (4 papers) and Sports Performance and Training (4 papers). The work is most often cited by research in Molecular Medicine (134 citations), Cancer Research (242 citations), Computer Vision and Pattern Recognition (330 citations), Signal Processing (117 citations) and Infectious Diseases (168 citations). Wei‐Yao Wang has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Matt Feiszli, Du Tran, Tzong‐Shi Chiueh, Jun‐Ren Sun, Jang‐Jih Lu, Peng Lv, Guifang Zhao, Wen-Chih Peng, Donghai Zhao and Tein-Yao Chang. Their work appears in journals such as PLoS ONE, Journal of Microbiology Immunology and Infection, Journal of Antimicrobial Chemotherapy, Cell Death Discovery and ACM Transactions on Intelligent Systems and Technology.

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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