Dianhai Yu

2.8k total citations · 1 hit paper
28 papers, 1.1k citations indexed

About

Dianhai Yu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Dianhai Yu has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Information Systems. Recurrent topics in Dianhai Yu's work include Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Speech Recognition and Synthesis (6 papers). Dianhai Yu is often cited by papers focused on Topic Modeling (10 papers), Natural Language Processing Techniques (9 papers) and Speech Recognition and Synthesis (6 papers). Dianhai Yu collaborates with scholars based in China, United States and France. Dianhai Yu's co-authors include Daxiang Dong, Hua Wu, Wei He, Haifeng Wang, Yanjun Ma, Haifeng Wang, Xiangyang Zhou, Ying Chen, Li Lü and Yi Liu and has published in prestigious journals such as IEEE Transactions on Cybernetics, Neurocomputing and Neural Networks.

In The Last Decade

Dianhai Yu

27 papers receiving 995 citations

Hit Papers

Multi-Task Learning for Multiple Language Translation 2015 2026 2018 2022 2015 100 200 300
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. Multi-Task Learning for Multiple Language Translation
    2015 316 citations Daxiang Dong, Hua Wu 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
Dianhai Yu China 13 846 301 129 51 32 28 1.1k
Jiajun Chen China 21 1.2k 1.4× 343 1.1× 111 0.9× 61 1.2× 41 1.3× 126 1.4k
Yue Hu China 16 599 0.7× 285 0.9× 225 1.7× 60 1.2× 25 0.8× 69 811
Mingming Sun China 15 373 0.4× 388 1.3× 141 1.1× 71 1.4× 44 1.4× 67 787
Kurt Driessens Netherlands 15 601 0.7× 193 0.6× 60 0.5× 46 0.9× 25 0.8× 52 852
Xiubo Geng China 14 545 0.6× 276 0.9× 222 1.7× 36 0.7× 60 1.9× 42 798
Jianpeng Cheng United Kingdom 9 612 0.7× 247 0.8× 88 0.7× 23 0.5× 64 2.0× 15 881
Gongshen Liu China 17 602 0.7× 364 1.2× 199 1.5× 103 2.0× 87 2.7× 93 1.1k
Misha Denil United Kingdom 8 460 0.5× 329 1.1× 56 0.4× 33 0.6× 30 0.9× 13 731

Countries citing papers authored by Dianhai Yu

Since Specialization
Citations

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

Fields of papers citing papers by Dianhai Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dianhai Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Dianhai Yu. A scholar is included among the top collaborators of Dianhai Yu 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 Dianhai Yu. Dianhai Yu 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.
Wei, Zhewei, et al.. (2024). Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials. 685–696. 3 indexed citations
2.
Cui, Shiyao, Zhenyu Zhang, Tingwen Liu, et al.. (2024). NACL: A General and Effective KV Cache Eviction Framework for LLM at Inference Time. 7913–7926. 1 indexed citations
3.
Liu, Ji, Zhihua Wu, Xuefeng Yao, et al.. (2023). HeterPS: Distributed deep learning with reinforcement learning based scheduling in heterogeneous environments. Future Generation Computer Systems. 148. 106–117. 29 indexed citations
4.
Zhang, Jinghui, Shikun Feng, Yu Sun, et al.. (2023). Label Information Enhanced Fraud Detection against Low Homophily in Graphs. arXiv (Cornell University). 406–416. 25 indexed citations
5.
Bian, Jiang, et al.. (2023). PGLBox: Multi-GPU Graph Learning Framework for Web-Scale Recommendation. 4262–4272. 4 indexed citations
6.
Tang, Siliang, et al.. (2023). Attribute-driven streaming edge partitioning with reconciliations for distributed graph neural network training. Neural Networks. 165. 987–998. 3 indexed citations
7.
Yang, Yang, et al.. (2022). Exploiting Cross-Modal Prediction and Relation Consistency for Semisupervised Image Captioning. IEEE Transactions on Cybernetics. 54(2). 890–902. 24 indexed citations
8.
Zhang, Hui, Yuan Tian, Junkun Chen, et al.. (2022). PaddleSpeech: An Easy-to-Use All-in-One Speech Toolkit. 114–123. 12 indexed citations
9.
Yu, Dianhai, et al.. (2022). TA-MoE: Topology-Aware Large Scale Mixture-Of-Expert Training. 22173–22186.
10.
Wang, Huijuan, Hui Zhong, Zhengjie Huang, et al.. (2022). Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 2755–2761. 13 indexed citations
11.
Liu, Ji, Daxiang Dong, Xi Wang, et al.. (2022). Large‐scale knowledge distillation with elastic heterogeneous computing resources. Concurrency and Computation Practice and Experience. 35(26). 5 indexed citations
12.
Niu, Guocheng, et al.. (2018). A New Method of Region Embedding for Text Classification. International Conference on Learning Representations. 31 indexed citations
13.
Zhou, Xiangyang, Li Lü, Daxiang Dong, et al.. (2018). Multi-Turn Response Selection for Chatbots with Deep Attention Matching Network. 1118–1127. 184 indexed citations
14.
Zhou, Xiangyang, Daxiang Dong, Hua Wu, et al.. (2016). Multi-view Response Selection for Human-Computer Conversation. 372–381. 130 indexed citations
15.
Dong, Daxiang, Hua Wu, Wei He, Dianhai Yu, & Haifeng Wang. (2015). Multi-Task Learning for Multiple Language Translation. 1723–1732. 316 indexed citations breakdown →
16.
Yu, Mo, Tiejun Zhao, Yalong Bai, Hao Tian, & Dianhai Yu. (2013). Cross-lingual Projections between Languages from Different Families. Meeting of the Association for Computational Linguistics. 2. 312–317. 3 indexed citations
17.
Zhou, Jie, Yu Sun, Zhanyi Liu, et al.. (2013). Generalization of Words for Chinese Dependency Parsing. 73–81. 4 indexed citations
18.
Yu, Mo, Tiejun Zhao, Daxiang Dong, Hao Tian, & Dianhai Yu. (2013). Compound Embedding Features for Semi-supervised Learning. North American Chapter of the Association for Computational Linguistics. 563–568. 17 indexed citations
19.
Lin, Xiaojun, Liang Zhao, Dianhai Yu, & Xihong Wu. (2010). Distributed training for Conditional Random Fields. 1–6. 4 indexed citations
20.
Wu, Xihong, et al.. (2008). An Improved CRF based Chinese Language Processing System for SIGHAN Bakeoff 2007. International Joint Conference on Natural Language Processing. 155–160. 3 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Jiajun Chen Breakdown of academic impact, for papers by Yue Hu Breakdown of academic impact, for papers by Mingming Sun Breakdown of academic impact, for papers by Kurt Driessens Breakdown of academic impact, for papers by Xiubo Geng Breakdown of academic impact, for papers by Jianpeng Cheng Breakdown of academic impact, for papers by Gongshen Liu Breakdown of academic impact, for papers by Misha Denil
Rankless by CCL
2026