Chi-kiu Lo

928 total citations
39 papers, 443 citations indexed

About

Chi-kiu Lo is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Chi-kiu Lo has authored 39 papers receiving a total of 443 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 2 papers in Computational Theory and Mathematics. Recurrent topics in Chi-kiu Lo's work include Natural Language Processing Techniques (37 papers), Topic Modeling (35 papers) and Text Readability and Simplification (15 papers). Chi-kiu Lo is often cited by papers focused on Natural Language Processing Techniques (37 papers), Topic Modeling (35 papers) and Text Readability and Simplification (15 papers). Chi-kiu Lo collaborates with scholars based in Hong Kong, Canada and United States. Chi-kiu Lo's co-authors include Dekai Wu, Michel Simard, Patrick Littell, Cyril Goutte, Eric Joanis, Rebecca Knowles, Roland Kühn, Tom Kocmi, Brian J. Thompson and Marine Carpuat and has published in prestigious journals such as Language Resources and Evaluation, NPARC and Rare & Special e-Zone (The Hong Kong University of Science and Technology).

In The Last Decade

Chi-kiu Lo

37 papers receiving 377 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chi-kiu Lo Hong Kong 12 441 65 33 17 8 39 443
Raymond Hendy Susanto Singapore 7 473 1.1× 69 1.1× 36 1.1× 12 0.7× 7 0.9× 10 493
Shexia He China 9 370 0.8× 70 1.1× 13 0.4× 31 1.8× 5 0.6× 10 381
Larraitz Uria Spain 7 380 0.9× 58 0.9× 17 0.5× 35 2.1× 7 0.9× 18 398
Rajen Chatterjee Italy 12 441 1.0× 90 1.4× 43 1.3× 25 1.5× 17 2.1× 24 448
Vitaly Nikolaev United States 3 245 0.6× 67 1.0× 24 0.7× 10 0.6× 3 0.4× 3 254
Frédéric Blain United Kingdom 10 280 0.6× 40 0.6× 39 1.2× 15 0.9× 17 2.1× 31 289
Markus Freitag Germany 11 469 1.1× 92 1.4× 31 0.9× 14 0.8× 12 1.5× 38 492
Dragos Stefan Munteanu United States 8 508 1.2× 49 0.8× 47 1.4× 44 2.6× 29 3.6× 9 527
Maria Nădejde United Kingdom 10 369 0.8× 112 1.7× 25 0.8× 21 1.2× 12 1.5× 21 391
Shamil Chollampatt Singapore 9 340 0.8× 52 0.8× 29 0.9× 8 0.5× 3 0.4× 11 361

Countries citing papers authored by Chi-kiu Lo

Since Specialization
Citations

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

Fields of papers citing papers by Chi-kiu Lo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chi-kiu Lo. 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 Chi-kiu Lo. The network helps show where Chi-kiu Lo may publish in the future.

Co-authorship network of co-authors of Chi-kiu Lo

This figure shows the co-authorship network connecting the top 25 collaborators of Chi-kiu Lo. A scholar is included among the top collaborators of Chi-kiu Lo 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 Chi-kiu Lo. Chi-kiu Lo 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
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Lo, Chi-kiu, et al.. (2024). Calibration and context in human evaluation of machine translation. NPARC. 31(4). 1017–1041.
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Freitag, Markus, Daniel Deutsch, Chi-kiu Lo, et al.. (2024). Are LLMs Breaking MT Metrics? Results of the WMT24 Metrics Shared Task. 47–81. 1 indexed citations
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Joanis, Eric, et al.. (2020). The Nunavut Hansard Inuktitut-English Parallel Corpus 3.0 with Preliminary Machine Translation Results.. Language Resources and Evaluation. 2562–2572. 20 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2014). On the reliability and inter-annotator agreement of human semantic MT evaluation via HMEANT. Language Resources and Evaluation. 602–607. 2 indexed citations
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Lo, Chi-kiu, et al.. (2013). Improving machine translation by training against an automatic semantic frame based evaluation metric. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 375–381. 14 indexed citations
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Lo, Chi-kiu, et al.. (2012). Accuracy and robustness in measuring the lexical similarity of semantic role fillers for automatic semantic MT evaluation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 574–581. 7 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2012). Unsupervised vs. supervised weight estimation for semantic MT evaluation metrics. Meeting of the Association for Computational Linguistics. 49–56. 12 indexed citations
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Lo, Chi-kiu, et al.. (2012). Fully Automatic Semantic MT Evaluation. Workshop on Statistical Machine Translation. 243–252. 41 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2011). MEANT: An inexpensive, high-accuracy, semi-automatic metric for evaluating translation utility based on semantic roles. Meeting of the Association for Computational Linguistics. 1. 220–229. 55 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2011). Structured vs. Flat Semantic Role Representations for Machine Translation Evaluation. Meeting of the Association for Computational Linguistics. 10–20. 11 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2011). SMT versus AI redux: how semantic fames evaluate MT more accurately. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1838–1845. 6 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2010). Evaluating Machine Translation Utility via Semantic Role Labels. Language Resources and Evaluation. 8 indexed citations
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Lo, Chi-kiu & Dekai Wu. (2010). Semantic vs. Syntactic vs. N-gram Structure for Machine Translation Evaluation. International Conference on Computational Linguistics. 52–60. 6 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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