Dawei Yin

5.2k total citations · 8 hit papers
66 papers, 2.7k citations indexed

About

Dawei Yin is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Dawei Yin has authored 66 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 38 papers in Information Systems and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Dawei Yin's work include Topic Modeling (30 papers), Recommender Systems and Techniques (29 papers) and Advanced Graph Neural Networks (20 papers). Dawei Yin is often cited by papers focused on Topic Modeling (30 papers), Recommender Systems and Techniques (29 papers) and Advanced Graph Neural Networks (20 papers). Dawei Yin collaborates with scholars based in China, Hong Kong and United States. Dawei Yin's co-authors include Qing Li, Wenqi Fan, Jiliang Tang, Yao Ma, Yuan He, Eric Zhao, Lianghao Xia, Chao Huang, Jiashu Zhao and Yong Xu and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Neural Networks and Machine Learning.

In The Last Decade

Dawei Yin

60 papers receiving 2.6k citations

Hit Papers

Graph Neural Networks for Social Recommendation 2019 2026 2021 2023 2019 2022 2024 2022 2024 250 500 750 1000
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. Graph Neural Networks for Social Recommendation
    2019 1.1k citations Wenqi Fan, Yao Ma et al. profile →
  2. Hypergraph Contrastive Collaborative Filtering
    2022 249 citations Lianghao Xia, Jiashu Zhao et al. profile →
  3. A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
    2024 137 citations Wenqi Fan, Yujuan Ding et al. profile →
  4. Contrastive Meta Learning with Behavior Multiplicity for Recommendation
    2022 117 citations Wei Wei, Chao Huang et al. profile →
  5. LLMRec: Large Language Models with Graph Augmentation for Recommendation
    2024 87 citations Wei Wei, Xubin Ren et al. profile →
  6. Representation Learning with Large Language Models for Recommendation
    2024 69 citations Xubin Ren, Wei Wei et al. The HKU Scholars Hub (University of Hong Kong) profile →
  7. GraphGPT: Graph Instruction Tuning for Large Language Models
    2024 57 citations Jiabin Tang, Yuhao Yang et al. profile →
  8. UrbanGPT: Spatio-Temporal Large Language Models
    2024 53 citations Lianghao Xia, Jiabin Tang et al. The HKU Scholars Hub (University of Hong Kong) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dawei Yin China 19 2.0k 1.6k 493 309 281 66 2.7k
Wenqi Fan Hong Kong 21 1.9k 1.0× 1.3k 0.8× 422 0.9× 276 0.9× 240 0.9× 70 2.6k
Chen Gao China 25 1.5k 0.8× 1.6k 1.0× 463 0.9× 215 0.7× 148 0.5× 95 2.5k
Fangzhao Wu China 37 3.5k 1.8× 2.1k 1.3× 644 1.3× 306 1.0× 160 0.6× 118 4.2k
Parham Moradi Iran 28 1.9k 1.0× 1.1k 0.7× 941 1.9× 389 1.3× 423 1.5× 108 3.2k
Lianghao Xia Hong Kong 27 1.6k 0.8× 1.6k 1.0× 416 0.8× 162 0.5× 148 0.5× 52 2.3k
Meng Jiang United States 31 2.2k 1.1× 1.2k 0.7× 404 0.8× 554 1.8× 615 2.2× 127 3.5k
Fuzheng Zhang China 22 3.6k 1.9× 3.0k 1.9× 852 1.7× 354 1.1× 323 1.1× 52 4.7k
Xiuqiang He China 27 1.6k 0.8× 1.7k 1.1× 744 1.5× 238 0.8× 99 0.4× 99 2.5k
Huan Zhao China 17 1.0k 0.5× 977 0.6× 346 0.7× 226 0.7× 174 0.6× 46 1.6k
Jianxin Li China 26 1.8k 0.9× 691 0.4× 315 0.6× 419 1.4× 311 1.1× 132 2.4k

Countries citing papers authored by Dawei Yin

Since Specialization
Citations

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

Fields of papers citing papers by Dawei Yin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dawei Yin

This figure shows the co-authorship network connecting the top 25 collaborators of Dawei Yin. A scholar is included among the top collaborators of Dawei Yin 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 Dawei Yin. Dawei Yin 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.
2.
Wu, Kesheng, Zhiao Shi, Shuaiqiang Wang, et al.. (2025). Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization. 19456–19472. 1 indexed citations
3.
Wang, Shijie, Wenqi Fan, Hui Liu, et al.. (2025). Graph Machine Learning in the Era of Large Language Models (LLMs). ACM Transactions on Intelligent Systems and Technology. 16(5). 1–40. 6 indexed citations
4.
5.
Lin, Xixun, Yanan Cao, Lixin Zou, et al.. (2025). Contrastive Modality-Disentangled Learning for Multimodal Recommendation. ACM Transactions on Information Systems. 43(3). 1–31. 11 indexed citations
6.
Sheng, Jiawei, et al.. (2025). Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation. 719–728. 1 indexed citations
7.
Su, Lixin, et al.. (2025). Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-Agent LLMs. ACM Transactions on Information Systems. 43(6). 1–33.
8.
Li, Yuchen, Haoyi Xiong, Linghe Kong, et al.. (2024). GS2P: a generative pre-trained learning to rank model with over-parameterization for web-scale search. Machine Learning. 113(8). 5331–5349. 5 indexed citations
9.
Fan, Wenqi, Yujuan Ding, Liangbo Ning, et al.. (2024). A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models. 6491–6501. 137 indexed citations breakdown →
10.
Xiong, Haoyi, 将尚 渡辺, Yuchen Li, et al.. (2024). When Search Engine Services Meet Large Language Models: Visions and Challenges. IEEE Transactions on Services Computing. 17(6). 4558–4577. 19 indexed citations
11.
Wei, Wei, Xubin Ren, Jiabin Tang, et al.. (2024). LLMRec: Large Language Models with Graph Augmentation for Recommendation. 806–815. 87 indexed citations breakdown →
12.
Tang, Jiabin, Yuhao Yang, Wei Wei, et al.. (2024). GraphGPT: Graph Instruction Tuning for Large Language Models. 491–500. 57 indexed citations breakdown →
13.
Cai, Qingpeng, Xiangyu Zhao, Xin Xin, et al.. (2024). AgentIR: 1st Workshop on Agent-based Information Retrieval. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3025–3028. 1 indexed citations
14.
Ren, Xubin, Wei Wei, Lianghao Xia, et al.. (2024). Representation Learning with Large Language Models for Recommendation. The HKU Scholars Hub (University of Hong Kong). 3464–3475. 69 indexed citations breakdown →
15.
Liu, Yiding, Qingyao Ai, Zhijing Wu, et al.. (2024). Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback. 48–58. 2 indexed citations
16.
Zou, Lixin, et al.. (2024). Toward Bias-Agnostic Recommender Systems: A Universal Generative Framework. ACM Transactions on Information Systems. 42(6). 1–30. 4 indexed citations
17.
Liu, Yiding, Qingyao Ai, Haitao Li, et al.. (2023). I3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval. 441–451. 3 indexed citations
18.
Lin, Xixun, Chuan Zhou, Jia Wu, et al.. (2023). Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation. IEEE Transactions on Knowledge and Data Engineering. 36(4). 1815–1828. 8 indexed citations
19.
Huang, Chao, Jiashu Zhao, & Dawei Yin. (2021). Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks. 2488–2498. 3 indexed citations
20.
Fan, Wenqi, Yao Ma, Qing Li, et al.. (2020). A Graph Neural Network Framework for Social Recommendations. IEEE Transactions on Knowledge and Data Engineering. 34(5). 2033–2047. 142 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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