Lifeng Shang

6.3k total citations · 1 hit paper
83 papers, 2.1k citations indexed

About

Lifeng Shang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Lifeng Shang has authored 83 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Artificial Intelligence, 32 papers in Computer Vision and Pattern Recognition and 9 papers in Information Systems. Recurrent topics in Lifeng Shang's work include Topic Modeling (41 papers), Natural Language Processing Techniques (36 papers) and Multimodal Machine Learning Applications (17 papers). Lifeng Shang is often cited by papers focused on Topic Modeling (41 papers), Natural Language Processing Techniques (36 papers) and Multimodal Machine Learning Applications (17 papers). Lifeng Shang collaborates with scholars based in China, Sweden and Hong Kong. Lifeng Shang's co-authors include Xin Jiang, Qun Liu, Yichun Yin, Xiao Dong Chen, Xiaoqi Jiao, Linlin Li, Fang Wang, Kwok-Ping Chan, Lu Hou and Hang Li and has published in prestigious journals such as IEEE Transactions on Image Processing, Journal of Food Engineering and Medicine.

In The Last Decade

Lifeng Shang

78 papers receiving 2.0k 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.

TinyBERT: Distilling BERT for Natural Language Understanding

2020 840 citations Xiaoqi Jiao, Yichun Yin et al. profile →

Peers

Lifeng Shang

AI

CVPR

IS

SP

EEE

Li Dong China

Lantao Yu United States

Zhaopeng Tu China

Angela Fan United States

Rico Sennrich Switzerland

Qun Liu China

Rohini K. Srihari United States

Jilian Zhang China

Deyi Xiong China

Li Dong China

Lifeng Shang

2.3k ×1.5

AI

643 ×0.7

CVPR

366 ×1.4

IS

130 ×1.1

SP

74 ×0.7

EEE

Citations per year, relative to Lifeng Shang Lifeng Shang (= 1×) peers Li Dong

Countries citing papers authored by Lifeng Shang

Since Specialization

Citations

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

Fields of papers citing papers by Lifeng Shang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lifeng Shang

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

Zhang, Jiebin, Yifan Song, Cuiping Kuang, et al.. (2025). More Tokens, Lower Precision: Towards the Optimal Token-Precision Trade-off in KV Cache Compression. 8092–8105.

2.

Zeng, Xingshan, Yuxin Jiang, Yufei Wang, et al.. (2024). MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 20153–20177. 3 indexed citations

3.

Jiang, Yuxin, Yufei Wang, Xingshan Zeng, et al.. (2024). FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4667–4688. 2 indexed citations

4.

Jiang, Yuxin, Chuhan Wu, Wanjun Zhong, et al.. (2024). Learning to Edit: Aligning LLMs with Knowledge Editing. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4689–4705. 4 indexed citations

5.

Zhong, Wanjun, Jiahui Gao, Weiwen Liu, et al.. (2024). Planning, Creation, Usage: Benchmarking LLMs for Comprehensive Tool Utilization in Real-World Complex Scenarios. 4363–4400. 4 indexed citations

6.

Bai, Haoli, Lu Hou, Lifeng Shang, et al.. (2024). Visually Guided Generative Text-Layout Pre-training for Document Intelligence. 4713–4730. 3 indexed citations

7.

Zeng, Xingshan, Yufei Wang, Yuxin Jiang, et al.. (2024). M4LE: A Multi-Ability Multi-Range Multi-Task Multi-Domain Long-Context Evaluation Benchmark for Large Language Models. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 15568–15592. 2 indexed citations

8.

Shang, Lifeng, et al.. (2023). Study of a Random Warranty Model Maintaining Fairness and a Random Replacement Next Model Sustaining Post-Warranty Reliability. Axioms. 12(3). 258–258. 2 indexed citations

9.

Wang, Weichao, Hongru Wang, Fei Mi, et al.. (2023). Improving Factual Consistency for Knowledge-Grounded Dialogue Systems via Knowledge Enhancement and Alignment. 7829–7844. 3 indexed citations

10.

Zhou, Jiawei, Lifeng Shang, Hao Jiang, et al.. (2022). Hyperlink-induced Pre-training for Passage Retrieval in Open-domain Question Answering. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 7135–7146. 9 indexed citations

11.

Li, Jian, Jieming Zhu, Guohao Cai, et al.. (2022). MINER: Multi-Interest Matching Network for News Recommendation. Findings of the Association for Computational Linguistics: ACL 2022. 343–352. 37 indexed citations

12.

Tao, Chaofan, Lu Hou, Wei Zhang, et al.. (2022). Compression of Generative Pre-trained Language Models via Quantization. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 4821–4836. 31 indexed citations

13.

Shen, Jianhao, Yichun Yin, Lin Li, et al.. (2021). Generate & Rank: A Multi-task Framework for Math Word Problems. Greater South Information System. 2269–2279. 21 indexed citations

14.

Shang, Lifeng, et al.. (2021). A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answering. 4111–4124. 3 indexed citations

15.

Hou, Lu, Jiacheng Sun, Lifeng Shang, et al.. (2021). Improved OOD Generalization via Adversarial Training and Pretraing. International Conference on Machine Learning. 11987–11997. 8 indexed citations

16.

Hou, Lu, Zhiqi Huang, Lifeng Shang, et al.. (2020). DynaBERT: Dynamic BERT with Adaptive Width and Depth. Neural Information Processing Systems. 33. 9782–9793. 27 indexed citations

17.

Jiao, Xiaoqi, Yichun Yin, Lifeng Shang, et al.. (2020). TinyBERT: Distilling BERT for Natural Language Understanding. 4163–4174. 840 indexed citations breakdown →

18.

Li, Zichao, Xin Jiang, Lifeng Shang, & Hang Li. (2018). Paraphrase Generation with Deep Reinforcement Learning. 3865–3878. 102 indexed citations

19.

Ko, Tom, et al.. (2018). Meta Learning for Few-shot Keyword Spotting.. arXiv (Cornell University). 4 indexed citations

20.

Shang, Lifeng, Tetsuya Sakai, Zhengdong Lu, et al.. (2016). Overview of the NTCIR-12 Short Text Conversation Task.. NTCIR. 15 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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