Jackie Chi Kit Cheung

2.2k total citations
76 papers, 1.0k citations indexed

About

Jackie Chi Kit Cheung is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Jackie Chi Kit Cheung has authored 76 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Artificial Intelligence, 13 papers in Computer Vision and Pattern Recognition and 6 papers in Information Systems. Recurrent topics in Jackie Chi Kit Cheung's work include Topic Modeling (61 papers), Natural Language Processing Techniques (51 papers) and Advanced Text Analysis Techniques (14 papers). Jackie Chi Kit Cheung is often cited by papers focused on Topic Modeling (61 papers), Natural Language Processing Techniques (51 papers) and Advanced Text Analysis Techniques (14 papers). Jackie Chi Kit Cheung collaborates with scholars based in Canada, United States and Algeria. Jackie Chi Kit Cheung's co-authors include Yue Dong, Jiapeng Wu, Meng Cao, Gerald Penn, Giuseppe Carenini, Meng Cao, William L. Hamilton, Herke van Hoof, Lucy Vanderwende and Eric Crawford and has published in prestigious journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation and Transactions of the Association for Computational Linguistics.

In The Last Decade

Jackie Chi Kit Cheung

72 papers receiving 964 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jackie Chi Kit Cheung Canada	16	919	111	93	59	55	76	1.0k
Daling Wang China	16	713 0.8×	198 1.8×	119 1.3×	36 0.6×	25 0.5×	78	911
Lifu Huang United States	20	1.1k 1.1×	229 2.1×	151 1.6×	128 2.2×	79 1.4×	66	1.2k
Mikel Artetxe Spain	10	1.4k 1.5×	337 3.0×	115 1.2×	44 0.7×	49 0.9×	35	1.6k
Tejaswini Deoskar United Kingdom	7	579 0.6×	105 0.9×	93 1.0×	29 0.5×	69 1.3×	17	716
Bharat Ram Ambati India	9	675 0.7×	110 1.0×	100 1.1×	31 0.5×	67 1.2×	22	808
Peng Qi China	7	557 0.6×	63 0.6×	80 0.9×	40 0.7×	64 1.2×	24	635
Chenguang Zhu United States	19	1.0k 1.1×	312 2.8×	66 0.7×	31 0.5×	42 0.8×	44	1.2k
Bing Yin United States	11	362 0.4×	102 0.9×	112 1.2×	26 0.4×	27 0.5×	36	528
Fei Xia United States	16	820 0.9×	115 1.0×	71 0.8×	22 0.4×	187 3.4×	55	1.0k
Steffen Eger Germany	14	816 0.9×	142 1.3×	125 1.3×	28 0.5×	39 0.7×	74	993

Countries citing papers authored by Jackie Chi Kit Cheung

Since Specialization

Citations

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

Fields of papers citing papers by Jackie Chi Kit Cheung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jackie Chi Kit Cheung. 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 Jackie Chi Kit Cheung. The network helps show where Jackie Chi Kit Cheung may publish in the future.

Co-authorship network of co-authors of Jackie Chi Kit Cheung

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

All Works

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20 of 20 papers shown

Piantanida, Pablo, et al.. (2024). GLIMPSE: Pragmatically Informative Multi-Document Summarization for Scholarly Reviews. 12737–12752.

Blodgett, Su Lin, et al.. (2024). ECBD: Evidence-Centered Benchmark Design for NLP. 16349–16365. 1 indexed citations

Mousavi, Mehdi, et al.. (2024). Performance of generative pre-trained transformers (GPTs) in Certification Examination of the College of Family Physicians of Canada. Family Medicine and Community Health. 12(Suppl 1). e002626–e002626. 5 indexed citations

Rahimi, Samira Abbasgholizadeh, et al.. (2023). Qualitative Code Suggestion: A Human-Centric Approach to Qualitative Coding. eScholarship@McGill (McGill). 14887–14909. 1 indexed citations

Cao, Meng, et al.. (2023). Analyzing Multi-Sentence Aggregation in Abstractive Summarization via the Shapley Value. 121–134.

Cao, Meng, et al.. (2022). Learning with Rejection for Abstractive Text Summarization. 9768–9780. 8 indexed citations

Xu, Peng, Wei Yang, Chenyang Huang, et al.. (2021). Optimizing Deeper Transformers on Small Datasets. 2089–2102. 35 indexed citations

Xu, Peng, Jackie Chi Kit Cheung, & Yanshuai Cao. (2020). On Variational Learning of Controllable Representations for Text without Supervision. International Conference on Machine Learning. 1. 10534–10543. 13 indexed citations

Xu, Peng, et al.. (2020). Optimizing Deeper Transformers on Small Datasets: An Application on Text-to-SQL Semantic Parsing.. arXiv (Cornell University). 2 indexed citations

10.

Cao, Meng, Yue Dong, Jiapeng Wu, & Jackie Chi Kit Cheung. (2020). Factual Error Correction for Abstractive Summarization Models. 6251–6258. 82 indexed citations

11.

Cao, Yanshuai, et al.. (2019). Preventing Posterior Collapse in Sequence VAEs with Pooling. arXiv (Cornell University).

12.

Cheung, Jackie Chi Kit, et al.. (2018). Constructing a Lexicon of Relational Nouns. Language Resources and Evaluation. 2 indexed citations

13.

Meunier, Jean-Guy, et al.. (2017). Computer-Assisted Conceptual Analysis of Textual Data as Applied to Philosophical Corpuses.. DH. 1 indexed citations

14.

Cheung, Jackie Chi Kit, et al.. (2016). Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs.. International Conference on Computational Linguistics. 2625–2634. 1 indexed citations

15.

Cheung, Jackie Chi Kit, et al.. (2015). Indicative Tweet Generation: An Extractive Summarization Problem?. 138–147. 6 indexed citations

16.

Cheung, Jackie Chi Kit & Gerald Penn. (2013). Probabilistic Domain Modelling With Contextualized Distributional Semantic Vectors. Meeting of the Association for Computational Linguistics. 392–401. 4 indexed citations

17.

Cheung, Jackie Chi Kit & Gerald Penn. (2013). Towards Robust Abstractive Multi-Document Summarization: A Caseframe Analysis of Centrality and Domain. Meeting of the Association for Computational Linguistics. 1233–1242. 13 indexed citations

18.

Cheung, Jackie Chi Kit & Gerald Penn. (2012). Unsupervised Detection of Downward-Entailing Operators By Maximizing Classification Certainty. Conference of the European Chapter of the Association for Computational Linguistics. 696–705. 3 indexed citations

19.

Cheung, Jackie Chi Kit & Gerald Penn. (2012). Evaluating Distributional Models of Semantics for Syntactically Invariant Inference. Conference of the European Chapter of the Association for Computational Linguistics. 33–43. 4 indexed citations

20.

Cheung, Jackie Chi Kit & Gerald Penn. (2010). Entity-Based Local Coherence Modelling Using Topological Fields. Meeting of the Association for Computational Linguistics. 186–195. 5 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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