Yinwei Wei

3.2k total citations · 3 hit papers
56 papers, 1.7k citations indexed

About

Yinwei Wei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Yinwei Wei has authored 56 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Computer Vision and Pattern Recognition, 34 papers in Artificial Intelligence and 26 papers in Information Systems. Recurrent topics in Yinwei Wei's work include Recommender Systems and Techniques (26 papers), Multimodal Machine Learning Applications (20 papers) and Advanced Graph Neural Networks (16 papers). Yinwei Wei is often cited by papers focused on Recommender Systems and Techniques (26 papers), Multimodal Machine Learning Applications (20 papers) and Advanced Graph Neural Networks (16 papers). Yinwei Wei collaborates with scholars based in China, Singapore and Australia. Yinwei Wei's co-authors include Liqiang Nie, Xiang Wang, Tat‐Seng Chua, Xiangnan He, Richang Hong, Xuemeng Song, Zhulin Tao, Xianglin Huang, Yan Li and Qi Li and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Knowledge and Data Engineering.

In The Last Decade

Yinwei Wei

54 papers receiving 1.7k 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.

MMGCN

2019 361 citations Yinwei Wei, Xiang Wang et al. National University of Singapore profile →
Contrastive Learning for Cold-Start Recommendation

2021 165 citations Yinwei Wei, Xiang Wang et al. profile →
Data-efficient Fine-tuning for LLM-based Recommendation

2024 46 citations Xinyu Lin, Wenjie Wang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yinwei Wei China	18	994	994	793	88	87	56	1.7k
Yelong Shen United States	17	477 0.5×	1.4k 1.4×	532 0.7×	63 0.7×	89 1.0×	50	1.8k
Da Cao China	16	449 0.5×	491 0.5×	488 0.6×	65 0.7×	38 0.4×	42	1.0k
Pipei Huang China	7	654 0.7×	549 0.6×	299 0.4×	125 1.4×	42 0.5×	10	952
Wang-Cheng Kang United States	9	1.4k 1.4×	1.1k 1.1×	730 0.9×	132 1.5×	92 1.1×	13	1.9k
Qinyong Wang China	15	1.2k 1.2×	1.1k 1.1×	330 0.4×	184 2.1×	74 0.9×	26	1.6k
Shiwen Wu China	5	628 0.6×	680 0.7×	208 0.3×	86 1.0×	31 0.4×	6	951
Lifeng Shang China	20	257 0.3×	1.5k 1.5×	896 1.1×	72 0.8×	117 1.3×	83	2.1k
Changhua Pei China	10	1.2k 1.2×	988 1.0×	380 0.5×	223 2.5×	99 1.1×	30	1.6k
Jitao Sang China	23	531 0.5×	645 0.6×	661 0.8×	135 1.5×	113 1.3×	91	1.4k

Countries citing papers authored by Yinwei Wei

Since Specialization

Citations

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

Fields of papers citing papers by Yinwei Wei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yinwei Wei

This figure shows the co-authorship network connecting the top 25 collaborators of Yinwei Wei. A scholar is included among the top collaborators of Yinwei Wei 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 Yinwei Wei. Yinwei Wei 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.

Zhang, Huaiwen, et al.. (2025). Multi-View User Preference Modeling for Personalized Text-to-Image Generation. IEEE Transactions on Multimedia. 27. 3082–3091.

2.

Li, Yongqi, Wenjie Wang, Leigang Qu, et al.. (2025). Revolutionizing Text-to-Image Retrieval as Autoregressive Token-to-Voken Generation. 813–822. 1 indexed citations

3.

Lin, Xinyu, Wenjie Wang, Yongqi Li, et al.. (2024). Data-efficient Fine-tuning for LLM-based Recommendation. 365–374. 46 indexed citations breakdown →

4.

Luo, Xin, et al.. (2024). POLISH: Adaptive Online Cross-Modal Hashing for Class Incremental Data. 4470–4478. 2 indexed citations

5.

Fernandez-Nieto, Gloria Milena, Zachari Swiecki, Yi‐Shan Tsai, et al.. (2024). Co-designing a knowledge management tool for educator communities of practice. Designing Interactive Systems Conference. 1970–1990. 3 indexed citations

6.

Ji, Wei, et al.. (2024). Weakly Supervised Video Moment Retrieval via Location-irrelevant Proposal Learning. 1595–1603. 4 indexed citations

7.

Li, Bobo, Hao Fei, Fei Li, et al.. (2024). Revisiting Conversation Discourse for Dialogue Disentanglement. ACM Transactions on Information Systems. 43(1). 1–34. 2 indexed citations

8.

Wen, Haokun, Xuemeng Song, Xiaolin Chen, et al.. (2024). Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image Retrieval. arXiv (Cornell University). 229–239. 10 indexed citations

9.

Li, Zhenyang, Fan Liu, Yinwei Wei, et al.. (2024). Attribute-driven Disentangled Representation Learning for Multimodal Recommendation. 9660–9669. 3 indexed citations

10.

Wei, Yinwei, et al.. (2024). Muti-Modal Emotion Recognition via Hierarchical Knowledge Distillation. IEEE Transactions on Multimedia. 26. 9036–9046. 11 indexed citations

11.

Jing, Peiguang, et al.. (2023). StyleEDL: Style-Guided High-order Attention Network for Image Emotion Distribution Learning. 853–861. 3 indexed citations

12.

Ji, Wei, et al.. (2023). Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation. 955–965. 13 indexed citations

13.

Wang, Wenjie, et al.. (2023). General Debiasing for Multimodal Sentiment Analysis. 5861–5869. 17 indexed citations

14.

Wei, Yinwei, et al.. (2023). LightGT: A Light Graph Transformer for Multimedia Recommendation. 1508–1517. 24 indexed citations

15.

Nie, Liqiang, et al.. (2023). Toward Fine-Grained Talking Face Generation. IEEE Transactions on Image Processing. 32. 5794–5807. 1 indexed citations

16.

Wei, Yinwei, et al.. (2022). Causal Inference for Knowledge Graph Based Recommendation. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11153–11164. 23 indexed citations

17.

Wang, Xiao, Tian Gan, Yinwei Wei, et al.. (2022). Micro-video Tagging via Jointly Modeling Social Influence and Tag Relation. Proceedings of the 30th ACM International Conference on Multimedia. 4478–4486. 5 indexed citations

18.

Liu, Meng, et al.. (2022). Siamese Alignment Network for Weakly Supervised Video Moment Retrieval. IEEE Transactions on Multimedia. 25. 3921–3933. 32 indexed citations

19.

Wang, Qifan, et al.. (2021). DualGNN: Dual Graph Neural Network for Multimedia Recommendation. IEEE Transactions on Multimedia. 25. 1074–1084. 109 indexed citations

20.

Wei, Yinwei, Xiang Wang, Liqiang Nie, Xiangnan He, & Tat‐Seng Chua. (2020). Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback. National University of Singapore. 3541–3549. 169 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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