Shengding Hu

8.6k total citations · 4 hit papers
17 papers, 4.6k citations indexed

About

Shengding Hu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Shengding Hu has authored 17 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 1 paper in Statistical and Nonlinear Physics. Recurrent topics in Shengding Hu's work include Topic Modeling (12 papers), Natural Language Processing Techniques (8 papers) and Multimodal Machine Learning Applications (4 papers). Shengding Hu is often cited by papers focused on Topic Modeling (12 papers), Natural Language Processing Techniques (8 papers) and Multimodal Machine Learning Applications (4 papers). Shengding Hu collaborates with scholars based in China, United States and Sweden. Shengding Hu's co-authors include Maosong Sun, Zhiyuan Liu, Cheng Yang, Ganqu Cui, Jie Zhou, Changcheng Li, Zhengyan Zhang, Lifeng Wang, Lifeng Wang and Juanzi Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nature Machine Intelligence and arXiv (Cornell University).

In The Last Decade

Shengding Hu

13 papers receiving 4.5k citations

Hit Papers

Graph neural networks: A review of methods and applications 2018 2026 2020 2023 2020 2018 2023 2022 1000 2.0k 3.0k
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: A review of methods and applications
    2020 3.2k citations Jie Zhou, Ganqu Cui et al. SHILAP Revista de lepidopterología profile →
  2. Graph Neural Networks: A Review of Methods and Applications
    2018 767 citations Jie Zhou, Ganqu Cui et al. arXiv (Cornell University) profile →
  3. Parameter-efficient fine-tuning of large-scale pre-trained language models
    2023 420 citations Ning Ding, Yujia Qin et al. Nature Machine Intelligence profile →
  4. Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
    2022 147 citations Shengding Hu, Ning Ding et al. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shengding Hu China 7 2.3k 767 577 497 460 17 4.6k
Ganqu Cui China 8 2.0k 0.9× 677 0.9× 532 0.9× 465 0.9× 431 0.9× 20 4.2k
Zhengyan Zhang China 16 2.7k 1.2× 847 1.1× 597 1.0× 528 1.1× 486 1.1× 35 4.9k
M. Gori Italy 4 2.8k 1.2× 1.3k 1.6× 652 1.1× 533 1.1× 582 1.3× 6 5.3k
Markus Hagenbuchner Australia 17 3.1k 1.4× 1.5k 1.9× 820 1.4× 566 1.1× 637 1.4× 62 6.1k
Cheng Yang China 28 3.5k 1.6× 1.0k 1.4× 1.2k 2.1× 677 1.4× 681 1.5× 148 6.5k
Gabriele Monfardini Italy 7 3.4k 1.5× 1.6k 2.1× 770 1.3× 612 1.2× 675 1.5× 8 6.4k
Takuya Akiba Japan 14 1.2k 0.5× 603 0.8× 246 0.4× 304 0.6× 401 0.9× 25 4.1k
Álex Rodríguez Italy 21 1.9k 0.8× 1.1k 1.4× 302 0.5× 978 2.0× 300 0.7× 70 4.8k
Peilin Zhao China 44 3.5k 1.5× 1.9k 2.5× 983 1.7× 731 1.5× 546 1.2× 171 6.6k
Zhao Li China 36 4.3k 1.9× 1.1k 1.4× 1.3k 2.2× 409 0.8× 1.1k 2.3× 450 7.2k

Countries citing papers authored by Shengding Hu

Since Specialization
Citations

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

Fields of papers citing papers by Shengding Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shengding Hu

This figure shows the co-authorship network connecting the top 25 collaborators of Shengding Hu. A scholar is included among the top collaborators of Shengding Hu 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 Shengding Hu. Shengding Hu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Hu, Shengding, Weilin Zhao, Huadong Wang, et al.. (2025). Optimal RoPE extension via Bayesian Optimization for training-free length generalization. SHILAP Revista de lepidopterología. 6. 1–11.
2.
Hu, Shengding, Yujie Huang, Yuxiang Zhang, et al.. (2024). OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems. 3828–3850. 6 indexed citations
3.
Hu, Shengding, et al.. (2024). UltraEval: A Lightweight Platform for Flexible and Comprehensive Evaluation for LLMs. 247–257. 2 indexed citations
4.
Zhang, Xinrong, Shengding Hu, Zihang Xu, et al.. (2024). Beyond the Turn-Based Game: Enabling Real-Time Conversations with Duplex Models. 11543–11557.
5.
Hu, Shengding, et al.. (2024). LEGENT: Open Platform for Embodied Agents. 335–345. 2 indexed citations
6.
Zhang, Xinrong, Shengding Hu, Zihang Xu, et al.. (2024). ∞Bench: Extending Long Context Evaluation Beyond 100K Tokens. 15262–15277. 4 indexed citations
7.
Ding, Ning, Yulin Chen, Bokai Xu, et al.. (2023). Enhancing Chat Language Models by Scaling High-quality Instructional Conversations. 3029–3051. 39 indexed citations
8.
Chen, Yulin, Ning Ding, Xiaobin Wang, et al.. (2023). Exploring Lottery Prompts for Pre-trained Language Models. 15428–15444.
9.
Ding, Ning, Yujia Qin, Guang Yang, et al.. (2023). Parameter-efficient fine-tuning of large-scale pre-trained language models. Nature Machine Intelligence. 5(3). 220–235. 420 indexed citations breakdown →
10.
Su, Yusheng, Chi-Min Chan, Jiali Cheng, et al.. (2023). Exploring the Impact of Model Scaling on Parameter-Efficient Tuning. 15062–15078.
11.
Hu, Shengding, et al.. (2023). Won’t Get Fooled Again: Answering Questions with False Premises. 5626–5643. 2 indexed citations
12.
Hu, Shengding, Ning Ding, Weilin Zhao, et al.. (2023). OpenDelta: A Plug-and-play Library for Parameter-efficient Adaptation of Pre-trained Models. 274–281. 3 indexed citations
13.
Hu, Shengding, Ning Ding, Huadong Wang, et al.. (2022). Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2225–2240. 147 indexed citations breakdown →
14.
Peng, Hao, Xiaozhi Wang, Shengding Hu, et al.. (2022). COPEN: Probing Conceptual Knowledge in Pre-trained Language Models. 5015–5035. 8 indexed citations
15.
Zhou, Jie, Shengding Hu, Xin Lv, et al.. (2021). KACC: A Multi-task Benchmark for Knowledge Abstraction, Concretization and Completion. 1751–1763. 4 indexed citations
16.
Zhou, Jie, Ganqu Cui, Shengding Hu, et al.. (2020). Graph neural networks: A review of methods and applications. SHILAP Revista de lepidopterología. 1. 57–81. 3221 indexed citations breakdown →
17.
Zhou, Jie, Ganqu Cui, Shengding Hu, et al.. (2018). Graph Neural Networks: A Review of Methods and Applications. arXiv (Cornell University). 767 indexed citations breakdown →

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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