Tong Xu

4.3k total citations · 1 hit paper
149 papers, 2.2k citations indexed

About

Tong Xu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Tong Xu has authored 149 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 89 papers in Artificial Intelligence, 53 papers in Computer Vision and Pattern Recognition and 45 papers in Information Systems. Recurrent topics in Tong Xu's work include Topic Modeling (43 papers), Recommender Systems and Techniques (33 papers) and Multimodal Machine Learning Applications (29 papers). Tong Xu is often cited by papers focused on Topic Modeling (43 papers), Recommender Systems and Techniques (33 papers) and Multimodal Machine Learning Applications (29 papers). Tong Xu collaborates with scholars based in China, United States and Hong Kong. Tong Xu's co-authors include Enhong Chen, Hui Xiong, Hengshu Zhu, Sirui Zhao, Chuan Qin, Chen Zhu, Jingbo Zhou, Dejing Dou, Shukang Yin and Shuangli Li and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Access and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Tong Xu

133 papers receiving 2.2k citations

Hit Papers

A survey on multimodal large language models 2024 2026 2025 2024 50 100 150
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. A survey on multimodal large language models
    2024 189 citations Sirui Zhao, Tong Xu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tong Xu China 26 1.2k 527 468 186 184 149 2.2k
Chuxu Zhang United States 21 2.1k 1.8× 421 0.8× 805 1.7× 187 1.0× 110 0.6× 79 3.2k
Shaojie Qiao China 26 793 0.7× 363 0.7× 364 0.8× 173 0.9× 134 0.7× 142 2.2k
Jinlan Fu China 15 2.1k 1.8× 538 1.0× 439 0.9× 108 0.6× 41 0.2× 28 2.9k
Ziyu Guan China 28 1.6k 1.4× 1.1k 2.0× 923 2.0× 81 0.4× 78 0.4× 133 2.9k
Simon Colton United Kingdom 11 1.2k 1.0× 356 0.7× 344 0.7× 95 0.5× 194 1.1× 32 2.1k
Sergio Ramírez‐Gallego Spain 16 933 0.8× 216 0.4× 363 0.8× 94 0.5× 93 0.5× 21 1.7k
Xu Sun China 33 2.7k 2.3× 934 1.8× 443 0.9× 169 0.9× 69 0.4× 116 3.3k
Xipeng Qiu China 37 5.1k 4.4× 1.1k 2.1× 803 1.7× 251 1.3× 72 0.4× 194 6.1k

Countries citing papers authored by Tong Xu

Since Specialization
Citations

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

Fields of papers citing papers by Tong Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tong Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Tong Xu. A scholar is included among the top collaborators of Tong Xu 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 Tong Xu. Tong Xu 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.
Wang, Wanyu, Xiangyu Zhao, Yang Yu, et al.. (2025). GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems. 1948–1959. 1 indexed citations
2.
Cao, Shaosheng, Tong Xu, Zuozhu Liu, et al.. (2025). PaRT: Enhancing Proactive Social Chatbots with Personalized Real-Time Retrieval. 4269–4274.
3.
Xu, Tong, et al.. (2025). Decremental Dynamics Planning for Robot Navigation. 4559–4565.
4.
Zhao, Sirui, et al.. (2025). MER-CLIP: AU-Guided Vision-Language Alignment for Micro-Expression Recognition. IEEE Transactions on Affective Computing. 16(4). 3028–3042.
5.
Zhang, Ziheng, Zhihong Zhu, Zhenxi Lin, et al.. (2024). Mitigating Hallucinations of Large Language Models in Medical Information Extraction via Contrastive Decoding. 7744–7757. 3 indexed citations
6.
Chen, Wei, et al.. (2024). Double-Checker: Large Language Model as a Checker for Few-shot Named Entity Recognition. 3172–3181. 1 indexed citations
7.
Hao, Yanbin, et al.. (2024). CVLP-NaVD: Contrastive Visual-language Pre-training Models for Non-annotated Visual Description. ACM Transactions on Multimedia Computing Communications and Applications. 21(11). 1–23.
8.
Xiong, Feiyu, et al.. (2024). CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models. ACM Transactions on Information Systems. 43(2). 1–32. 26 indexed citations
9.
Zeng, Xiaoyi, et al.. (2024). Large Language Model based Long-tail Query Rewriting in Taobao Search. 20–28. 13 indexed citations
10.
11.
Wu, Zhize, Pengpeng Sun, Keke Tang, et al.. (2024). SelfGCN: Graph Convolution Network With Self-Attention for Skeleton-Based Action Recognition. IEEE Transactions on Image Processing. 33. 4391–4403. 13 indexed citations
12.
Chen, Liyi, Chuan Qin, Ying Sun, et al.. (2024). Collaboration-Aware Hybrid Learning for Knowledge Development Prediction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3976–3985. 8 indexed citations
13.
Sun, Ying, Chuan Qin, Le Zhang, et al.. (2024). Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph. ACM Transactions on Information Systems. 42(4). 1–28. 3 indexed citations
14.
Xu, Lixiang, et al.. (2024). Graph Augmentation Empowered Contrastive Learning for Recommendation. ACM Transactions on Information Systems. 43(2). 1–27. 3 indexed citations
15.
Xu, Tong, et al.. (2023). Multi-Grained Multimodal Interaction Network for Entity Linking. 1583–1594. 7 indexed citations
16.
Xu, Tong, et al.. (2023). Comprehending the Gossips: Meme Explanation in Time-Sync Video Comment via Multimodal Cues. ACM Transactions on Asian and Low-Resource Language Information Processing. 22(8). 1–17. 2 indexed citations
17.
Wu, Han, et al.. (2023). Hierarchical Multi-Modal Attention Network for Time-Sync Comment Video Recommendation. IEEE Transactions on Circuits and Systems for Video Technology. 34(4). 2694–2705. 5 indexed citations
18.
Zhao, Sirui, et al.. (2023). DFME: A New Benchmark for Dynamic Facial Micro-Expression Recognition. IEEE Transactions on Affective Computing. 15(3). 1371–1386. 8 indexed citations
19.
Liu, Chuanren, et al.. (2022). Recent advances in domain-driven data mining. International Journal of Data Science and Analytics. 15(1). 1–7. 3 indexed citations
20.
Zhao, Sirui, et al.. (2022). PEDM: A Multi-task Learning Model for Persona-aware Emoji-embedded Dialogue Generation. ACM Transactions on Multimedia Computing Communications and Applications. 19(3s). 1–21. 8 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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