Ting Liu

10.2k total citations · 3 hit papers
127 papers, 5.8k citations indexed

About

Ting Liu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Ting Liu has authored 127 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Artificial Intelligence, 17 papers in Computer Vision and Pattern Recognition and 15 papers in Information Systems. Recurrent topics in Ting Liu's work include Topic Modeling (98 papers), Natural Language Processing Techniques (83 papers) and Advanced Text Analysis Techniques (30 papers). Ting Liu is often cited by papers focused on Topic Modeling (98 papers), Natural Language Processing Techniques (83 papers) and Advanced Text Analysis Techniques (30 papers). Ting Liu collaborates with scholars based in China, United States and Singapore. Ting Liu's co-authors include Bing Qin, Duyu Tang, Ming Zhou, Xiaocheng Feng, Furu Wei, Nan Yang, Wanxiang Che, Zhangyin Feng, Nan Duan and Linjun Shou and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and Neurocomputing.

In The Last Decade

Ting Liu

119 papers receiving 5.6k citations

Hit Papers

CodeBERT: A Pre-Trained Model for Programmi... 2014 2026 2018 2022 2020 2014 2016 400 800 1.2k
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. CodeBERT: A Pre-Trained Model for Programming and Natural Languages
    2020 1.4k citations Duyu Tang, Bing Qin et al. profile →
  2. Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification
    2014 781 citations Duyu Tang, Ming Zhou et al. profile →
  3. Aspect Level Sentiment Classification with Deep Memory Network
    2016 675 citations Duyu Tang, Bing Qin et al. profile →

Peers

Ting Liu
William B. Frakes United States
Hugo Zaragoza United Kingdom
Dipanjan Das United States
Gordon V. Cormack Canada
Xiaocheng Feng China
Alan Bundy United Kingdom
Hang Li China
Xintao Wu United States
Zhiyong Feng China
Zhenchang Xing Australia
William B. Frakes United States
Ting Liu
Citations per year, relative to Ting Liu Ting Liu (= 1×) peers William B. Frakes

Countries citing papers authored by Ting Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ting Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Liu. A scholar is included among the top collaborators of Ting Liu 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 Ting Liu. Ting Liu 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.
Cui, Yiming, Ting Liu, Wanxiang Che, Zhigang Chen, & Shijin Wang. (2022). ExpMRC: explainability evaluation for machine reading comprehension. Heliyon. 8(4). e09290–e09290. 7 indexed citations
2.
Zhang, Weinan, et al.. (2022). A Static and Dynamic Attention Framework for Multi Turn Dialogue Generation. ACM Transactions on Information Systems. 41(1). 1–30. 10 indexed citations
3.
Cui, Yiming, Ting Liu, Wanxiang Che, Zhigang Chen, & Shijin Wang. (2022). Teaching Machines to Read, Answer and Explain. IEEE/ACM Transactions on Audio Speech and Language Processing. 30. 1483–1492. 8 indexed citations
4.
Qin, Libo, Minheng Ni, Yue Zhang, et al.. (2022). Multi-domain Spoken Language Understanding Using Domain- and Task-aware Parameterization. ACM Transactions on Asian and Low-Resource Language Information Processing. 21(4). 1–17. 3 indexed citations
5.
Cui, Yiming, Weinan Zhang, Wanxiang Che, et al.. (2022). Multilingual multi-aspect explainability analyses on machine reading comprehension models. iScience. 25(5). 104176–104176. 4 indexed citations
6.
Cui, Yiming, Wanxiang Che, Ting Liu, et al.. (2022). Interactive Gated Decoder for Machine Reading Comprehension. ACM Transactions on Asian and Low-Resource Language Information Processing. 21(4). 1–19. 4 indexed citations
7.
Qin, Libo, Wanxiang Che, Minheng Ni, Yangming Li, & Ting Liu. (2021). Knowing Where to Leverage: Context-Aware Graph Convolutional Network With an Adaptive Fusion Layer for Contextual Spoken Language Understanding. IEEE/ACM Transactions on Audio Speech and Language Processing. 29. 1280–1289. 17 indexed citations
8.
Ma, Wentao, Yiming Cui, Chenglei Si, et al.. (2020). CharBERT: Character-aware Pre-trained Language Model. arXiv (Cornell University). 39–50. 45 indexed citations
9.
Tang, Duyu, Bing Qin, & Ting Liu. (2016). Aspect Level Sentiment Classification with Deep Memory Network. 214–224. 675 indexed citations breakdown →
10.
Guo, Jiang, Wanxiang Che, Haifeng Wang, Ting Liu, & Jun Xu. (2016). A Unified Architecture for Semantic Role Labeling and Relation Classification. International Conference on Computational Linguistics. 1264–1274. 8 indexed citations
11.
Zhao, Yanyan, Wanxiang Che, Honglei Guo, et al.. (2014). Sentence Compression for Target-Polarity Word Collocation Extraction. International Conference on Computational Linguistics. 1360–1369. 9 indexed citations
12.
Liu, Ting, Kit W. Cho, George Aaron Broadwell, et al.. (2014). Automatic Expansion of the MRC Psycholinguistic Database Imageability Ratings. Language Resources and Evaluation. 2800–2805. 7 indexed citations
13.
Ding, Xiao, Zhicheng Dou, Bing Qin, Ting Liu, & Ji-Rong Wen. (2013). Improving Web Search Ranking by Incorporating Structured Annotation of Queries. 468–478. 2 indexed citations
14.
Ding, Xiao, Bing Qin, & Ting Liu. (2013). Building Chinese Event Type Paradigm Based on Trigger Clustering. International Joint Conference on Natural Language Processing. 311–319. 2 indexed citations
15.
Liu, Ting. (2011). A Weighted Voting Based Automatic Term Recognition Method. Zhongwen xinxi xuebao. 1 indexed citations
16.
Song, Wei, Yu Zhang, Ting Liu, & Sheng Li. (2010). Bridging Topic Modeling and Personalized Search. International Conference on Computational Linguistics. 1167–1175. 15 indexed citations
17.
Zheng, Weihao, et al.. (2008). Topic tracking based on keywords dependency profile. 129–140. 5 indexed citations
18.
Yang, Xiaofeng, et al.. (2008). An Entity-Mention Model for Coreference Resolution with Inductive Logic Programming. National University of Singapore. 843–851. 46 indexed citations
19.
Zhao, Shiqi, Ming Zhou, & Ting Liu. (2007). Learning question paraphrases for QA from Encarta logs. International Joint Conference on Artificial Intelligence. 1795–1800. 19 indexed citations
20.
Weigang, Li, Ting Liu, Zhen Wang, & Sheng Li. (2004). Aligning Bilingual Corpora Using Sentences Location Information. Meeting of the Association for Computational Linguistics. 141–147. 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by William B. Frakes Breakdown of academic impact, for papers by Hugo Zaragoza Breakdown of academic impact, for papers by Dipanjan Das Breakdown of academic impact, for papers by Gordon V. Cormack Breakdown of academic impact, for papers by Xiaocheng Feng Breakdown of academic impact, for papers by Alan Bundy Breakdown of academic impact, for papers by Hang Li Breakdown of academic impact, for papers by Xintao Wu Breakdown of academic impact, for papers by Zhiyong Feng Breakdown of academic impact, for papers by Zhenchang Xing
Rankless by CCL
2026