Qipeng Guo

2.1k total citations · 1 hit paper
22 papers, 1.1k citations indexed

About

Qipeng Guo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Hardware and Architecture. According to data from OpenAlex, Qipeng Guo has authored 22 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 2 papers in Hardware and Architecture. Recurrent topics in Qipeng Guo's work include Topic Modeling (16 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (5 papers). Qipeng Guo is often cited by papers focused on Topic Modeling (16 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (5 papers). Qipeng Guo collaborates with scholars based in China, United States and Hong Kong. Qipeng Guo's co-authors include Xipeng Qiu, Xiangyang Xue, Zheng Zhang, Ruotian Ma, Linyang Li, Yunfan Shao, Hang Yan, Tao Gui, Junqi Dai and Pengfei Liu and has published in prestigious journals such as ACM Computing Surveys, IEEE/ACM Transactions on Audio Speech and Language Processing and Science China Information Sciences.

In The Last Decade

Qipeng Guo

21 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

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.

BERT-ATTACK: Adversarial Attack Against BERT Using BERT

2020 306 citations Linyang Li, Ruotian Ma et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qipeng Guo China	11	907	219	118	102	68	22	1.1k
André F. T. Martins Portugal	20	1.5k 1.6×	300 1.4×	144 1.2×	42 0.4×	44 0.6×	128	1.8k
Zexuan Zhong United States	12	698 0.8×	179 0.8×	118 1.0×	32 0.3×	71 1.0×	16	871
Yichun Yin China	10	907 1.0×	365 1.7×	99 0.8×	61 0.6×	34 0.5×	18	1.1k
Jiajun Chen China	21	1.2k 1.3×	343 1.6×	111 0.9×	41 0.4×	35 0.5×	126	1.4k
Wenhu Chen United States	19	793 0.9×	344 1.6×	97 0.8×	40 0.4×	84 1.2×	67	1.1k
Amarnag Subramanya United States	15	713 0.8×	218 1.0×	57 0.5×	159 1.6×	100 1.5×	30	907
Da Zheng United States	14	621 0.7×	416 1.9×	171 1.4×	32 0.3×	46 0.7×	42	929
Derek F. Wong Macao	21	1.0k 1.1×	317 1.4×	131 1.1×	56 0.5×	42 0.6×	132	1.4k
Zengfeng Huang China	12	487 0.5×	158 0.7×	128 1.1×	153 1.5×	29 0.4×	44	726
Bryan Kisiel United States	7	1.2k 1.4×	207 0.9×	309 2.6×	64 0.6×	199 2.9×	12	1.4k

Countries citing papers authored by Qipeng Guo

Since Specialization

Citations

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

Fields of papers citing papers by Qipeng Guo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qipeng Guo

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

Wang, Cunxiang, Xiaoze Liu, Qipeng Guo, et al.. (2025). Survey on Factuality in Large Language Models. ACM Computing Surveys. 58(1). 1–37. 2 indexed citations

2.

Yin, Zhangyue, et al.. (2024). Explicit Memory Learning with Expectation Maximization. 16618–16635. 1 indexed citations

3.

Ren, Jie, Qipeng Guo, Hang Yan, et al.. (2024). Identifying Semantic Induction Heads to Understand In-Context Learning. 6916–6932. 1 indexed citations

4.

Lv, Kai, Hang Yan, Qipeng Guo, Haijun Lv, & Xipeng Qiu. (2024). AdaLomo: Low-memory Optimization with Adaptive Learning Rate. 12486–12502. 4 indexed citations

5.

Cui, Fan, et al.. (2024). OriGen: Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection. 1–9. 11 indexed citations

6.

Guo, Qipeng, et al.. (2024). Knowledge-Centric Hallucination Detection. 6953–6975. 1 indexed citations

7.

Cheng, Jay J., Lin Qiu, Weiqi Wang, et al.. (2023). StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 11518–11537. 4 indexed citations

8.

Yin, Zhangyue, Cheng Chang, Qipeng Guo, et al.. (2023). Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model Communication. 15135–15153. 3 indexed citations

9.

Guo, Qipeng, et al.. (2023). Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus. 915–932. 5 indexed citations

10.

Zhang, Shuo, Keyu Chen, Yuqing Yang, et al.. (2023). CoLLiE: Collaborative Training of Large Language Models in an Efficient Way. 527–542. 2 indexed citations

11.

Yan, Hang, Tao Gui, Junqi Dai, et al.. (2021). A Unified Generative Framework for Various NER Subtasks. 5808–5822. 173 indexed citations

12.

Guo, Qipeng, Xipeng Qiu, Xiangyang Xue, & Zheng Zhang. (2021). Syntax-guided text generation via graph neural network. Science China Information Sciences. 64(5). 20 indexed citations

13.

Guo, Qipeng, Xipeng Qiu, Pengfei Liu, Xiangyang Xue, & Zheng Zhang. (2020). Multi-Scale Self-Attention for Text Classification. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 7847–7854. 47 indexed citations

14.

Li, Linyang, Ruotian Ma, Qipeng Guo, Xiangyang Xue, & Xipeng Qiu. (2020). BERT-ATTACK: Adversarial Attack Against BERT Using BERT. 6193–6202. 306 indexed citations breakdown →

15.

Sun, Tianxiang, Yunfan Shao, Xipeng Qiu, et al.. (2020). CoLAKE: Contextualized Language and Knowledge Embedding. 3660–3670. 97 indexed citations

16.

Jin, Zhijing, Qipeng Guo, Xipeng Qiu, & Zheng Zhang. (2020). GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text Generation. 2398–2409. 15 indexed citations

17.

Guo, Qipeng, Xipeng Qiu, Pengfei Liu, et al.. (2019). Star-Transformer. 1315–1325. 102 indexed citations

18.

Wang, Minjie, Lingfan Yu, Da Zheng, et al.. (2019). Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs. arXiv (Cornell University). 260 indexed citations

19.

Guo, Qipeng, Xipeng Qiu, Xiangyang Xue, & Zheng Zhang. (2019). Low-Rank and Locality Constrained Self-Attention for Sequence Modeling. IEEE/ACM Transactions on Audio Speech and Language Processing. 27(12). 2213–2222. 23 indexed citations

20.

Ye, Zihao, Qipeng Guo, Quan Gan, & Zheng Zhang. (2019). SegTree Transformer: Iterative refinement of hierarchical features. 1 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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