🧑‍🔬 Zheyuan Liu

🏛️ Affiliations

🎓Fuzhou UniversityFuzhou · China2021–2026 · 64 paperscurrent🎓University of Notre DameNotre Dame · United States2024–2026 · 9 paperscurrent🔬China Electric Power Research InstituteBeijing2023–2026 · 8 paperscurrent🎓Adelaide UniversityAdelaide · Australia2026 · 1 papercurrent🎓The University of AdelaideAdelaide · Australia2026 · 1 papercurrent🎓Tianjin UniversityTianjin · China2017–2021 · 19 papers🔬Collaborative Innovation Center of Chemical Science and Engineering TianjinTianjin · China2017–2020 · 12 papers🎓Australian National UniversityCanberra · Australia2021–2025 · 9 papers🎓Dalian University of TechnologyDalian · China2018–2023 · 9 papers🏛️Chinese Academy of SciencesBeijing · China2017–2024 · 8 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 28 more institutions on single bylines are not listed.

🧭 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning (2024 · 83 citations)
   Most current approaches to personalizing large language models work by putting user information into the prompt.
2. Towards Safer Large Language Models through Machine Unlearning (2024 · 71 citations)
   Large language models can still give dangerous answers to harmful prompts. Earlier unlearning methods based on gradient ascent suppress such answers but tend to damage replies to ordinary requests. The authors propose Selective Knowledge negation Unlearning (SKU), a two-stage framework that removes harmful knowledge…

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. Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuningConference on Empirical Methods in Natural Language Processing (EMNLP)Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, et al.2024 · 83 citations
2. Towards Safer Large Language Models through Machine UnlearningFindings of the Association for Computational LinguisticsZheyuan Liu, Guangyao Dou, Zhaoxuan Tan, et al.2024 · 71 citations
3. Personalized Pieces: Efficient Personalized Large Language Models through Collaborative EffortsProceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · original ↗ · no summary yetZhaoxuan Tan, Zheyuan Liu, Meng Jiang2024 · 39 citations
4. Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language ModelsProceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · original ↗ · no summary yetZheyuan Liu et al.2025 · 11 citations
5. Instant Personalized Large Language Model Adaptation via HypernetworkProceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · original ↗ · no summary yetZhaoxuan Tan et al.2026 · 2 citations

🤝 Co-authors here

5 co-authors with a page, the most papers together first.

• Meng Jiang ×2
• Yijun Tian ×2
• Zhaoxuan Tan ×2
• Bing Yin
• Qingkai Zeng

Venues

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

• Conference on Empirical Methods in Natural Language Processing (EMNLP) ×2: EMNLP 2024
• Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ×2
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2024

🔗 Cited by

Papers of our library cite their works 134 times (of the 141,840 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated 24 October 2026

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