Toby Jia-Jun Li

1.8k citations
64 papers · 722 indexed · 1 hit paper · h-index 16

Toby Jia-Jun Li

53 papers receiving 710 citations

Hit Papers

Limitations of the LLM-as-a-Judge Approach for Evaluating...172025202651015

Peers

Toby Jia-Jun Li
Comparison fields: 5 of 83
  • Human-Computer Interaction 141
  • Health Informatics 22
  • Software 40
  • Computer Science Applications 54
  • Artificial Intelligence 319
Replace Tongshuang Wu with:
Tongshuang Wu United States
J.D. Zamfirescu-Pereira United States
Justin D. Weisz United States
Joon Sung Park United States
Joseph O’Brien United States
Alexander Koller Germany
Noah Wardrip–Fruin United States
Rebecca Fiebrink United Kingdom
Matthew Butler Australia
Huahai Yang United States
Toby Jia-Jun Li relative to Tongshuang Wu United States Tongshuang Wu's profile →
Citations per field
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Tongshuang Wu · 1×
Citations per year

Countries citing papers authored by Toby Jia-Jun Li

Since Specialization
Citations

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

Fields of papers citing papers by Toby Jia-Jun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Toby Jia-Jun Li. 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 Toby Jia-Jun Li. The network helps show where Toby Jia-Jun Li may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Toby Jia-Jun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Toby Jia-Jun Li Line = papers co-authored together Toby Jia-Jun Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasksbreakdown →
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Interactive Task and Concept Learning from Natural Language Instructions and GUI Demonstrations
20191

About Toby Jia-Jun Li

Toby Jia-Jun Li is a scholar working on Human-Computer Interaction, Artificial Intelligence and Information Systems, having authored 64 papers that have together received 722 indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Software Engineering Research (10 papers), Speech and dialogue systems (9 papers), Natural Language Processing Techniques (9 papers), AI in Service Interactions (8 papers), Innovative Human-Technology Interaction (7 papers), Persona Design and Applications (5 papers) and Privacy, Security, and Data Protection (4 papers). The work is most often cited by research in Human-Computer Interaction (141 citations), Health Informatics (22 citations) and Software (40 citations). Toby Jia-Jun Li has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Brad A. Myers, Amos Azaria, Zheng Zhang, Oriana Riva, Haijun Xia, Daniel Ritchie, Ying Xu, Tongshuang Wu, Dakuo Wang and Bingsheng Yao. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, ACM Transactions on Interactive Intelligent Systems, ACM Transactions on Software Engineering and Methodology, Journal of Systems and Software and IEEE Transactions on Software Engineering.

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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