Pascale Fung

14.1k total citations · 2 hit papers
226 papers, 5.8k citations indexed

About

Pascale Fung is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Pascale Fung has authored 226 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 197 papers in Artificial Intelligence, 36 papers in Computer Vision and Pattern Recognition and 33 papers in Signal Processing. Recurrent topics in Pascale Fung's work include Natural Language Processing Techniques (129 papers), Topic Modeling (113 papers) and Speech Recognition and Synthesis (64 papers). Pascale Fung is often cited by papers focused on Natural Language Processing Techniques (129 papers), Topic Modeling (113 papers) and Speech Recognition and Synthesis (64 papers). Pascale Fung collaborates with scholars based in Hong Kong, United States and China. Pascale Fung's co-authors include Andrea Madotto, Tiezheng Yu, Dan Su, Ziwei Ji, Yan Xu, Nayeon Lee, Etsuko Ishii, Rita Frieske, Dario Bertero and Zhaojiang Lin and has published in prestigious journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Medical Imaging and ACM Computing Surveys.

In The Last Decade

Pascale Fung

213 papers receiving 5.3k citations

Hit Papers

Survey of Hallucination in Natural Language Generation 2022 2026 2023 2024 2022 2023 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pascale Fung Hong Kong 38 4.5k 722 494 481 390 226 5.8k
Diyi Yang United States 35 4.7k 1.0× 692 1.0× 1.1k 2.2× 286 0.6× 177 0.5× 169 7.0k
Yoav Goldberg Israel 37 6.8k 1.5× 1.0k 1.5× 800 1.6× 236 0.5× 132 0.3× 133 8.2k
Graham Neubig United States 41 6.6k 1.5× 1.8k 2.5× 1.2k 2.4× 417 0.9× 185 0.5× 280 8.1k
Johanna D. Moore United Kingdom 41 4.4k 1.0× 684 0.9× 527 1.1× 335 0.7× 60 0.2× 210 6.3k
Minlie Huang China 43 6.3k 1.4× 891 1.2× 1.1k 2.2× 221 0.5× 78 0.2× 205 7.3k
Simone Stumpf United Kingdom 27 1.8k 0.4× 441 0.6× 399 0.8× 94 0.2× 409 1.0× 89 3.9k
Bing Qin China 34 7.0k 1.6× 567 0.8× 2.1k 4.2× 535 1.1× 90 0.2× 236 8.8k
Nils Reimers Germany 13 4.1k 0.9× 920 1.3× 1.0k 2.1× 244 0.5× 61 0.2× 27 5.7k
Shafiq Joty Singapore 33 3.1k 0.7× 667 0.9× 1.1k 2.2× 213 0.4× 95 0.2× 180 4.4k
Hanna Wallach United States 26 3.0k 0.7× 411 0.6× 748 1.5× 206 0.4× 186 0.5× 67 4.9k

Countries citing papers authored by Pascale Fung

Since Specialization
Citations

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

Fields of papers citing papers by Pascale Fung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pascale Fung

This figure shows the co-authorship network connecting the top 25 collaborators of Pascale Fung. A scholar is included among the top collaborators of Pascale Fung 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 Pascale Fung. Pascale Fung 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.
Yu, Tiezheng, Ziwei Ji, & Pascale Fung. (2023). Improving Query-Focused Meeting Summarization with Query-Relevant Knowledge. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 48–54. 1 indexed citations
2.
Chung, Willy, Samuel Cahyawijaya, Bryan Wilie, Holy Lovenia, & Pascale Fung. (2023). InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systems. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 5 indexed citations
4.
Cahyawijaya, Samuel, et al.. (2022). SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 140–154. 3 indexed citations
5.
Madotto, Andrea, Zhaojiang Lin, Zhenpeng Zhou, et al.. (2021). Continual Learning in Task-Oriented Dialogue Systems. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 7452–7467. 48 indexed citations
6.
Lin, Zhaojiang, Andrea Madotto, Genta Indra Winata, & Pascale Fung. (2020). MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3391–3405. 82 indexed citations
7.
Yu, Tiezheng, Dan Su, Wenliang Dai, & Pascale Fung. (2020). Dimsum @LaySumm 20. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 303–309. 2 indexed citations
8.
Lee, Nayeon, Yejin Bang, Jamin Shin, & Pascale Fung. (2019). Understanding the Shades of Sexism in Popular TV Series. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 122–125. 1 indexed citations
9.
Park, Ji Ho, et al.. (2017). Emojive! Collecting Emotion Data from Speech and Facial Expression Using Mobile Game App.. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 827–828. 1 indexed citations
10.
Fung, Pascale, Farhad Bin Siddique, Ruixi Lin, et al.. (2016). Zara: A Virtual Interactive Dialogue System Incorporating Emotion, Sentiment and Personality Recognition. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 278–281. 12 indexed citations
11.
Wan, Yan, et al.. (2016). A Machine Learning based Music Retrieval and Recommendation System. Language Resources and Evaluation. 1970–1977. 2 indexed citations
12.
Fung, Pascale, et al.. (2014). A Hindi-English Code-Switching Corpus. Language Resources and Evaluation. 2410–2413. 39 indexed citations
13.
Li, Ying & Pascale Fung. (2012). Code Switching Language Model with Translation Constraint for Mixed Language Speech Recognition. International Conference on Computational Linguistics. 1671. 12 indexed citations
14.
Li, Ying & Pascale Fung. (2012). Code-Switch Language Model with Inversion Constraints for Mixed Language Speech Recognition. International Conference on Computational Linguistics. 1671–1680. 30 indexed citations
15.
Li, Ying, et al.. (2012). A Mandarin-English Code-Switching Corpus. Language Resources and Evaluation. 2515–2519. 27 indexed citations
16.
Liu, Yi, et al.. (2010). A Very Large Scale Mandarin Chinese Broadcast Corpus for GALE Project. Language Resources and Evaluation. 1 indexed citations
17.
Liu, Yi, et al.. (2010). A Very Large Scale Mandarin Chinese Broadcast Collection for the GALE Program. Language Resources and Evaluation. 1 indexed citations
18.
Fung, Pascale, et al.. (2004). Mining Very-Non-Parallel Corpora: Parallel Sentence and Lexicon Extraction via Bootstrapping and E. Empirical Methods in Natural Language Processing. 75. 57–63. 29 indexed citations
19.
Zheng, Fang, et al.. (2002). CASS: A phonetically transcribed corpus of Mandarin spontaneous speech. Cambridge University Engineering Department Publications Database. 16 indexed citations
20.
Fung, Pascale, et al.. (1998). Translating Unknown Words Using Nonparallel, Comparable Texts. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 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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