Zuohui Fu

1.8k total citations · 1 hit paper
31 papers, 731 citations indexed

About

Zuohui Fu is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zuohui Fu has authored 31 papers receiving a total of 731 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 15 papers in Information Systems and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zuohui Fu's work include Topic Modeling (18 papers), Recommender Systems and Techniques (15 papers) and Advanced Graph Neural Networks (10 papers). Zuohui Fu is often cited by papers focused on Topic Modeling (18 papers), Recommender Systems and Techniques (15 papers) and Advanced Graph Neural Networks (10 papers). Zuohui Fu collaborates with scholars based in United States, Germany and China. Zuohui Fu's co-authors include Yongfeng Zhang, Shijie Geng, Yingqiang Ge, Shuchang Liu, Gerard de Melo, Juntao Tan, Shuyuan Xu, Yikun Xian, Yunqi Li and Yi Zhang and has published in prestigious journals such as ACM Transactions on Information Systems, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Zuohui Fu

31 papers receiving 715 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.

Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)

2022 223 citations Shijie Geng, Shuchang Liu et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zuohui Fu United States	16	570	414	124	65	48	31	731
Yingqiang Ge United States	14	519 0.9×	451 1.1×	100 0.8×	104 1.6×	35 0.7×	27	722
Florian Tramèr United States	14	567 1.0×	170 0.4×	54 0.4×	33 0.5×	41 0.9×	32	754
Dong‐Kyu Chae South Korea	13	343 0.6×	383 0.9×	162 1.3×	71 1.1×	9 0.2×	56	624
Yu Lei Hong Kong	11	261 0.5×	310 0.7×	112 0.9×	86 1.3×	37 0.8×	15	481
Yeon-Chang Lee South Korea	12	266 0.5×	254 0.6×	131 1.1×	52 0.8×	9 0.2×	35	429
M. Shahriar Hossain United States	12	143 0.3×	89 0.2×	142 1.1×	22 0.3×	41 0.9×	39	411
Jianxin Ma China	10	448 0.8×	331 0.8×	127 1.0×	82 1.3×	11 0.2×	15	599
How Jing United States	6	378 0.7×	470 1.1×	140 1.1×	124 1.9×	18 0.4×	11	606
Vincent Bindschaedler United States	12	673 1.2×	171 0.4×	52 0.4×	17 0.3×	91 1.9×	21	779

Countries citing papers authored by Zuohui Fu

Since Specialization

Citations

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

Fields of papers citing papers by Zuohui Fu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zuohui Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Zuohui Fu. A scholar is included among the top collaborators of Zuohui Fu 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 Zuohui Fu. Zuohui Fu 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:

20 of 20 papers shown

1.

Ge, Yingqiang, Shuchang Liu, Zuohui Fu, et al.. (2024). A Survey on Trustworthy Recommender Systems. 3(2). 1–68. 17 indexed citations

2.

Tan, Juntao, et al.. (2023). A Reusable Model-agnostic Framework for Faithfully Explainable Recommendation and System Scrutability. ACM Transactions on Information Systems. 42(1). 1–29. 11 indexed citations

3.

Geng, Shijie, Juntao Tan, Shuchang Liu, Zuohui Fu, & Yongfeng Zhang. (2023). VIP5: Towards Multimodal Foundation Models for Recommendation. 9606–9620. 28 indexed citations

4.

Geng, Shijie, Zuohui Fu, Yingqiang Ge, et al.. (2022). Improving Personalized Explanation Generation through Visualization. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 244–255. 20 indexed citations

5.

Geng, Shijie, Zuohui Fu, Juntao Tan, et al.. (2022). Path Language Modeling over Knowledge Graphsfor Explainable Recommendation. Proceedings of the ACM Web Conference 2022. 946–955. 46 indexed citations

6.

Tan, Juntao, Shijie Geng, Zuohui Fu, et al.. (2022). Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning. Proceedings of the ACM Web Conference 2022. 1018–1027. 49 indexed citations

7.

Fu, Zuohui, et al.. (2022). D-HYPR. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2732–2742. 1 indexed citations

8.

Liu, Shuchang, Shuyuan Xu, Wenhui Yu, et al.. (2021). FedCT: Federated Collaborative Transfer for Recommendation. 716–725. 39 indexed citations

9.

Fu, Zuohui, Yikun Xian, Shuyuan Xu, et al.. (2021). HOOPS: Human-in-the-Loop Graph Reasoning for Conversational Recommendation. 2415–2421. 21 indexed citations

10.

Xu, Shuyuan, Yunqi Li, Shuchang Liu, et al.. (2021). Learning causal explanations for recommendation. 2911. 13–25. 5 indexed citations

11.

Shi, Lei, Kai Shuang, Shijie Geng, et al.. (2021). Dense Contrastive Visual-Linguistic Pretraining. 5203–5212. 7 indexed citations

12.

Fu, Zuohui, Yikun Xian, Shijie Geng, Gerard de Melo, & Yongfeng Zhang. (2021). Popcorn. 494–503. 11 indexed citations

13.

Xian, Yikun, Handong Zhao, Tak Yeon Lee, et al.. (2021). EXACTA: Explainable Column Annotation. 3775–3785. 6 indexed citations

14.

Hu, Zhe, Zuohui Fu, Yu Yin, & Gerard de Melo. (2021). Context-Aware Interaction Network for Question Matching. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 3846–3853. 1 indexed citations

15.

Fu, Zuohui, Yikun Xian, Yongfeng Zhang, & Yi Zhang. (2021). IUI 2021 Tutorial on Conversational Recommendation Systems. 1–2. 1 indexed citations

16.

Xian, Yikun, et al.. (2021). Faithfully Explainable Recommendation via Neural Logic Reasoning. 3083–3090. 21 indexed citations

17.

Liu, Bingchen, Yizhe Zhu, Zuohui Fu, Gerard de Melo, & Ahmed Elgammal. (2020). OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 4836–4843. 16 indexed citations

18.

Fu, Zuohui, Yikun Xian, Yongfeng Zhang, & Yi Zhang. (2020). Tutorial on Conversational Recommendation Systems. 751–753. 28 indexed citations

19.

Liu, Zhiqiang, Zuohui Fu, Jie Cao, et al.. (2019). Rhetorically Controlled Encoder-Decoder for Modern Chinese Poetry Generation. 1992–2001. 17 indexed citations

20.

Wang, Guang, Wenzhong Li, Jun Zhang, et al.. (2019). sharedCharging. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 3(3). 1–25. 38 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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