Sunhao Dai

435 total citations
15 papers, 67 citations indexed

About

Sunhao Dai is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research. According to data from OpenAlex, Sunhao Dai has authored 15 papers receiving a total of 67 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Information Systems and 6 papers in Management Science and Operations Research. Recurrent topics in Sunhao Dai's work include Recommender Systems and Techniques (8 papers), Advanced Bandit Algorithms Research (5 papers) and Topic Modeling (3 papers). Sunhao Dai is often cited by papers focused on Recommender Systems and Techniques (8 papers), Advanced Bandit Algorithms Research (5 papers) and Topic Modeling (3 papers). Sunhao Dai collaborates with scholars based in China and United States. Sunhao Dai's co-authors include Jun Xu, Ji-Rong Wen, Xiao Zhang, Zhenhua Dong, Quanyu Dai, Xiaochi Wei, Dawei Yin, Liang Pang, Shuaiqiang Wang and Hengyi Cai and has published in prestigious journals such as Frontiers of Computer Science, arXiv (Cornell University) and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

In The Last Decade

Sunhao Dai

13 papers receiving 67 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sunhao Dai China	5	39	35	15	9	5	15	67
Peitian Zhang China	2	43 1.1×	18 0.5×	9 0.6×	10 1.1×	5 1.0×	4	82
Enming Yuan China	3	48 1.2×	65 1.9×	25 1.7×	15 1.7×	3 0.6×	4	79
Zihui Gu China	4	44 1.1×	20 0.6×	11 0.7×	4 0.4×	4 0.8×	6	55
Maciej Janik United States	4	48 1.2×	32 0.9×	6 0.4×	7 0.8×	5 1.0×	5	65
Aditya Gupta United States	3	42 1.1×	11 0.3×	14 0.9×	13 1.4×	9 1.8×	7	67
Aman Madaan United States	5	107 2.7×	23 0.7×	9 0.6×	18 2.0×	6 1.2×	9	143
Danica Damljanović United Kingdom	5	80 2.1×	26 0.7×	12 0.8×	12 1.3×	8 1.6×	11	89
Florian Reinfrank Austria	3	33 0.8×	32 0.9×	8 0.5×	6 0.7×	8 1.6×	8	47
Pierre-Antoine Champin France	6	33 0.8×	29 0.8×	5 0.3×	10 1.1×	14 2.8×	18	70
Mohamed Amir Yosef Germany	4	90 2.3×	34 1.0×	13 0.9×	6 0.7×	2 0.4×	5	98

Countries citing papers authored by Sunhao Dai

Since Specialization

Citations

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

Fields of papers citing papers by Sunhao Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunhao Dai

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

15 of 15 papers shown

1.

Dai, Sunhao, et al.. (2025). Exploring the Escalation of Source Bias in User, Data, and Recommender System Feedback Loop. 1676–1686. 1 indexed citations

2.

Dai, Sunhao, et al.. (2025). Unifying Bias and Unfairness in Information Retrieval: New Challenges in the LLM Era. 998–1001. 3 indexed citations

3.

Dai, Sunhao, et al.. (2025). Mitigating Source Bias with LLM Alignment. 370–380. 1 indexed citations

4.

Du, Zhaocheng, et al.. (2025). Few-shot LLM Synthetic Data with Distribution Matching. 432–441.

5.

Dai, Sunhao, Xiaochi Wei, Hengyi Cai, et al.. (2025). Tool learning with large language models: a survey. Frontiers of Computer Science. 19(8). 13 indexed citations

6.

Dai, Sunhao, Jieming Zhu, Zhenhua Dong, et al.. (2024). Modeling User Attention in Music Recommendation. 761–774. 2 indexed citations

7.

Dai, Sunhao, Xiao Zhang, Yinfeng Li, et al.. (2024). SAQRec: Aligning Recommender Systems to User Satisfaction via Questionnaire Feedback. 3165–3175. 4 indexed citations

8.

Tang, Jiakai, Sunhao Dai, Xu Chen, et al.. (2024). Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning. arXiv (Cornell University). 2854–2865. 4 indexed citations

9.

Dai, Sunhao, et al.. (2024). Neural Retrievers are Biased Towards LLM-Generated Content. 526–537. 10 indexed citations

10.

Chen, Sirui, et al.. (2024). Reinforcing Long-Term Performance in Recommender Systems with User-Oriented Exploration Policy. 1850–1860. 4 indexed citations

11.

Dai, Sunhao, et al.. (2024). ReCODE: Modeling Repeat Consumption with Neural ODE. arXiv (Cornell University). 2599–2603. 4 indexed citations

12.

Dai, Sunhao, Yupeng Hou, Wayne Xin Zhao, et al.. (2024). Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method. arXiv (Cornell University). 3714–3723.

13.

Dai, Sunhao, Weihao Liu, Liang Pang, et al.. (2024). Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration. 7052–7074. 1 indexed citations

14.

Dai, Sunhao, et al.. (2023). Dually Enhanced Delayed Feedback Modeling for Streaming Conversion Rate Prediction. 390–399. 5 indexed citations

15.

Zhang, Xiao, Sunhao Dai, Jun Xu, et al.. (2022). Counteracting User Attention Bias in Music Streaming Recommendation via Reward Modification. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2504–2514. 15 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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