Hangbo Bao

3.7k total citations · 1 hit paper
8 papers, 432 citations indexed

About

Hangbo Bao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Informatics. According to data from OpenAlex, Hangbo Bao has authored 8 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Health Informatics. Recurrent topics in Hangbo Bao's work include Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers) and Multimodal Machine Learning Applications (4 papers). Hangbo Bao is often cited by papers focused on Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers) and Multimodal Machine Learning Applications (4 papers). Hangbo Bao collaborates with scholars based in China, India and United Kingdom. Hangbo Bao's co-authors include Furu Wei, Shaohan Huang, Li Dong, Wenhui Wang, Wenhui Wang, Saksham Singhal, Dong Li, Zhiliang Peng, Johan Björck and Subhojit Som and has published in prestigious journals such as International Journal of Machine Learning and Cybernetics, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and Neural Information Processing Systems.

In The Last Decade

Hangbo Bao

8 papers receiving 416 citations

Hit Papers

align trajectories

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.

Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks

2023 247 citations Wenhui Wang, Hangbo Bao et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hangbo Bao China	5	279	231	23	19	18	8	432
Saksham Singhal China	7	368 1.3×	289 1.3×	20 0.9×	9 0.5×	15 0.8×	10	507
Litao Yu Australia	8	174 0.6×	262 1.1×	31 1.3×	18 0.9×	23 1.3×	27	399
S. Chitrakala India	10	306 1.1×	162 0.7×	53 2.3×	21 1.1×	12 0.7×	52	497
Mitchell Wortsman United States	6	286 1.0×	328 1.4×	20 0.9×	7 0.4×	23 1.3×	9	513
Mehdi Rezagholizadeh Canada	9	257 0.9×	143 0.6×	12 0.5×	27 1.4×	7 0.4×	53	373
Juhua Hu United States	9	246 0.9×	249 1.1×	10 0.4×	7 0.4×	18 1.0×	27	390
А.В. Куракин United States	6	284 1.0×	151 0.7×	14 0.6×	13 0.7×	23 1.3×	8	361
Vivek Sharma Germany	7	220 0.8×	332 1.4×	15 0.7×	7 0.4×	19 1.1×	14	436
Xiaohu Cheng China	6	187 0.7×	104 0.5×	23 1.0×	16 0.8×	20 1.1×	9	273

Countries citing papers authored by Hangbo Bao

Since Specialization

Citations

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

Fields of papers citing papers by Hangbo Bao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hangbo Bao. 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 Hangbo Bao. The network helps show where Hangbo Bao may publish in the future.

Co-authorship network of co-authors of Hangbo Bao

This figure shows the co-authorship network connecting the top 25 collaborators of Hangbo Bao. A scholar is included among the top collaborators of Hangbo Bao 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 Hangbo Bao. Hangbo Bao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Bao, Hangbo, et al.. (2023). Fine-tuning pretrained transformer encoders for sequence-to-sequence learning. International Journal of Machine Learning and Cybernetics. 15(5). 1711–1728. 10 indexed citations

2.

Wang, Wenhui, Hangbo Bao, Dong Li, et al.. (2023). Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks. 19175–19186. 247 indexed citations breakdown →

3.

Bao, Hangbo, Shaohan Huang, Dong Li, et al.. (2022). THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption. Findings of the Association for Computational Linguistics: ACL 2022. 3510–3520. 42 indexed citations

4.

Zhang, Shengqiang, Xingxing Zhang, Hangbo Bao, & Furu Wei. (2022). Attention Temperature Matters in Abstractive Summarization Distillation. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 127–141. 9 indexed citations

5.

Wang, Wenhui, Hangbo Bao, Shaohan Huang, Li Dong, & Furu Wei. (2021). MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers. 2140–2151. 115 indexed citations

6.

Hao, Yaru, Li Dong, Hangbo Bao, Ke Xu, & Furu Wei. (2021). Learning to Sample Replacements for ELECTRA Pre-Training. 4495–4506. 4 indexed citations

7.

Wang, Wenhui, Furu Wei, Li Dong, et al.. (2020). MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers. Neural Information Processing Systems. 33. 5776–5788. 3 indexed citations

8.

Bao, Hangbo, Li Dong, Furu Wei, et al.. (2019). Inspecting Unification of Encoding and Matching with Transformer: A Case Study of Machine Reading Comprehension. 14–18. 2 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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