Li Dong

8.0k total citations · 2 hit papers
63 papers, 2.8k citations indexed

About

Li Dong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Li Dong has authored 63 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 11 papers in Information Systems. Recurrent topics in Li Dong's work include Topic Modeling (35 papers), Natural Language Processing Techniques (33 papers) and Multimodal Machine Learning Applications (15 papers). Li Dong is often cited by papers focused on Topic Modeling (35 papers), Natural Language Processing Techniques (33 papers) and Multimodal Machine Learning Applications (15 papers). Li Dong collaborates with scholars based in China, United States and United Kingdom. Li Dong's co-authors include Mirella Lapata, Furu Wei, Jianpeng Cheng, Ke Xu, Ming Zhou, Duyu Tang, Chuanqi Tan, Shaohan Huang, Yaru Hao and Zewen Chi and has published in prestigious journals such as Information Sciences, Applied Soft Computing and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Li Dong

56 papers receiving 2.7k 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.

Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification

2014 708 citations Li Dong, Furu Wei et al. profile →
Long Short-Term Memory-Networks for Machine Reading

2016 664 citations Jianpeng Cheng, Li Dong et al. Edinburgh Research Explorer (University of Edinburgh) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Li Dong China	18	2.3k	643	366	130	79	63	2.8k
Zhengbao Jiang United States	11	1.8k 0.8×	508 0.8×	485 1.3×	107 0.8×	132 1.7×	16	2.6k
Lifeng Shang China	20	1.5k 0.6×	896 1.4×	257 0.7×	117 0.9×	60 0.8×	83	2.1k
Liping Jing China	24	1.5k 0.6×	806 1.3×	452 1.2×	167 1.3×	68 0.9×	137	2.2k
Aslı Çelikyılmaz United States	28	2.7k 1.1×	790 1.2×	266 0.7×	81 0.6×	178 2.3×	109	3.2k
Ankur P. Parikh United States	11	1.7k 0.7×	609 0.9×	268 0.7×	95 0.7×	71 0.9×	31	2.0k
Weizhe Yuan United States	5	1.4k 0.6×	411 0.6×	344 0.9×	85 0.7×	107 1.4×	13	2.1k
Rohini K. Srihari United States	24	1.6k 0.7×	741 1.2×	553 1.5×	213 1.6×	108 1.4×	131	2.5k
Jakob Uszkoreit United States	17	2.6k 1.1×	1.0k 1.6×	328 0.9×	207 1.6×	78 1.0×	23	3.1k
Marco Turchi Italy	26	2.4k 1.0×	372 0.6×	260 0.7×	157 1.2×	47 0.6×	136	2.8k

Countries citing papers authored by Li Dong

Since Specialization

Citations

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

Fields of papers citing papers by Li Dong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Li Dong

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

Guo, Xiaoli, Yanjun Zuo, & Li Dong. (2025). When auditing Meets Blockchain: A study on applying blockchain smart contracts in auditing. International Journal of Accounting Information Systems. 56. 100730–100730. 3 indexed citations

2.

Li, Dahua, et al.. (2024). Short-term photovoltaic power combination prediction based on DBO-VMD and CPO-LSTM. Journal of Physics Conference Series. 2823(1). 12056–12056.

3.

Dong, Li, et al.. (2024). PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11381–11389.

4.

He, Xu, et al.. (2024). Improving Unsupervised Hierarchical Representation With Reinforcement Learning. 22946–22956.

5.

Dong, Li, et al.. (2024). Bayesian framework based additive intrinsic components optimization deformable model for image segmentation. Signal Processing Image Communication. 131. 117238–117238.

6.

Dong, Li, et al.. (2024). Maximizing discrimination masking for faithful question answering with machine reading. Information Processing & Management. 62(1). 103915–103915. 2 indexed citations

7.

Dong, Li & Haichao Zheng. (2023). Soft imitation reinforcement learning with value decomposition for portfolio management. Applied Soft Computing. 151. 111108–111108. 3 indexed citations

8.

Yang, Jian, Shuming Ma, Li Dong, et al.. (2023). GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator. 3 indexed citations

9.

Dong, Li, et al.. (2023). Intelligent Operation and Maintenance Schedule System Based on Knowledge Graph: Construction and Applications. 177–181. 1 indexed citations

10.

Dong, Li, Barun Patra, Shuming Ma, et al.. (2023). A Length-Extrapolatable Transformer. 14590–14604. 26 indexed citations

11.

Ji, Wanting, et al.. (2023). A composite blockchain associated event traceability method for financial activities. Peer-to-Peer Networking and Applications. 16(4). 1696–1715. 2 indexed citations

12.

Wang, Wenhui, Hangbo Bao, Shaohan Huang, Li Dong, & Furu Wei. (2021). MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers. 2140–2151. 115 indexed citations

13.

Chi, Zewen, Li Dong, Furu Wei, et al.. (2021). InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training. 3576–3588. 143 indexed citations

14.

Chi, Zewen, Li Dong, Furu Wei, Xian-Ling Mao, & Heyan Huang. (2020). Can Monolingual Pretrained Models Help Cross-Lingual Classification?. 12–17. 2 indexed citations

15.

Hao, Yaru, Li Dong, Furu Wei, & Ke Xu. (2019). Visualizing and Understanding the Effectiveness of BERT. 4141–4150. 90 indexed citations

16.

Dong, Li & Mirella Lapata. (2018). Coarse-to-Fine Decoding for Neural Semantic Parsing. Edinburgh Research Explorer (University of Edinburgh). 731–742. 206 indexed citations

17.

Dong, Li, Shaohan Huang, Furu Wei, et al.. (2017). Learning to Generate Product Reviews from Attributes. Edinburgh Research Explorer. 623–632. 115 indexed citations

18.

Cheng, Jianpeng, Li Dong, & Mirella Lapata. (2016). Long Short-Term Memory-Networks for Machine Reading. Edinburgh Research Explorer (University of Edinburgh). 551–561. 664 indexed citations breakdown →

19.

Dong, Li, Furu Wei, Chuanqi Tan, et al.. (2014). Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification. 49–54. 708 indexed citations breakdown →

20.

Dong, Li. (2009). Transformation from MapInfo file to SVG in WebGIS application. Jisuanji yingyong yanjiu. 2 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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