🧑‍🔬 Yuan-Fang Li

🏛️ Affiliations

🎓Monash UniversityMelbourne · Australia2011–2026 · 200 papersEmployment since 2011 · Lecturer, Faculty of Information TechnologyEmployment since 2016 · Senior Lecturer, Faculty of Information Technologycurrent🎓The University of SydneySydney · Australia2026 · 1 papercurrent🎓National University of SingaporeSingapore · Singapore2002–2008 · 23 papers🎓The University of QueenslandBrisbane · Australia2008–2014 · 13 papers🎓Swinburne University of TechnologyMelbourne · Australia2021–2023 · 4 papers🎓Southeast UniversityNanjing · China2022–2025 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Time-LLM: Time Series Forecasting by Reprogramming Large Language Models (2023 · 77 citations)
   Forecasting models for time series are usually built for a single task or domain. Pre-trained foundation models for this data type are scarce because large training collections are lacking. Time-LLM tackles this by adapting an existing large language model to forecasting while leaving all of its weights frozen.
2. MedDCR: Learning to Design Agentic Workflows for Medical Coding (2026 · 2 citations)
   Assigning ICD codes to clinical notes involves several reasoning stages: spotting diagnoses, consulting code indexes, enforcing guideline rules and checking consistency.

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages ↗Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 · no summary yetTahmid Hasan et al.2021 · 502 citations
2. Time-LLM: Time Series Forecasting by Reprogramming Large Language ModelsarXiv:2310.01728Ming Jin, Shiyu Wang, Lintao Ma, et al.2023 · 77 citations
3. Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs ↗neural information processing systems · no summary yetMing Jin, Yuan-Fang Li, Shirui Pan2022 · 59 citations
4. Paraphrasing Techniques for Maritime QA system ↗arXiv:2203.10854 · no summary yetFatemeh Shiri et al.2022 · 16 citations
5. MedDCR: Learning to Design Agentic Workflows for Medical CodingFindings of the Association for Computational LinguisticsJiyang Zheng, Islam Nassar, Thanh Vu, et al.2026 · 2 citations

🤝 Co-authors here

12 of 13 co-authors with a page, the most papers together first.

• Islam Nassar
• James Y. Zhang
• Lintao Ma
• Ming Jin
• Pin-Yu Chen
• Qingsong Wen
• Shirui Pan
• Shiyu Wang
• Thanh Vu
• Tongliang Liu
• Xiaoming Shi
• Yuxuan Liang

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
• Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
• neural information processing systems

🔗 Cited by

Papers of our library cite their works 367 times (of the 149,439 papers whose bibliographies we read); 75 citing papers with a page here →.

Updated 2 November 2026

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