🧑‍🔬 Honglei Zhuang

🏛️ Affiliations

🏢GoogleMountain View · United States2020–2025 · 40 papers🎓University of Illinois Urbana-ChampaignUrbana · United States2014–2020 · 19 papers🎓Tsinghua UniversityBeijing · China2009–2013 · 5 papersEducation 2009–2013 · Bachelor, Computer Science and Technology🎓University of WaterlooWaterloo · Canada2023–2024 · 2 papers🎓University of Massachusetts AmherstAmherst Center · United States2023 · 2 papers

🏛️University of Illinois at Urbana-ChampaignUrbana · United States2013–2019Education 2013–2019 · PhD, Computer Science

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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. Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting (2024 · 300 citations)
   The paper addresses why off-the-shelf LLMs have struggled to rank documents for a query as well as fine-tuned rankers.
2. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning (2021 · 114 citations)
   Multi-task learning helps transfer in NLP, but no one had systematically tested what happens when the number of supervised tasks used during pre-training is pushed very high.

All works

7 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. Large Language Models are Effective Text Rankers with Pairwise Ranking PromptingFindings of the Association for Computational LinguisticsZhen Qin, Rolf Jagerman, Kai Hui, et al.2024 · 300 citations
2. ExT5: Towards Extreme Multi-Task Scaling for Transfer LearningarXiv:2111.10952Vamsi Aribandi, Yi Tay, Tal Schuster, et al.2021 · 114 citations
3. Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees ↗International Conference on Learning Representations · no summary yetZhen Qin et al.2021 · 56 citations
4. Debiasing Crowdsourced Batches ↗ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetHonglei Zhuang et al.2015 · 23 citations
5. ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inference ↗Findings of the Association for Computational Linguistics: ACL 2022 · no summary yetKai Hui et al.2022 · 12 citations
6. Born Again Neural Rankers. ↗arXiv (Cornell University) · no summary yetZhen Qin et al.2021 · 4 citations
7. SAE ↗ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yetYang Yang et al.2013

🤝 Co-authors here

12 of 18 co-authors with a page, the most papers together first.

• Kai Hui ×2
• Dara Bahri
• Donald Metzler
• Huaixiu Steven Zheng
• Jai Gupta
• Jialu Liu
• Jiaming Shen
• Jianmo Ni
• Jinfeng Rao
• Junru Wu
• Michael Bendersky
• Sanket Vaibhav Mehta

Venues

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

• ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) ×2
• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2024
• Findings of the Association for Computational Linguistics: ACL 2022
• International Conference on Learning Representations

🔗 Cited by

Papers of our library cite their works 278 times (of the 149,439 papers whose bibliographies we read); 57 citing papers with a page here →.

Updated 2 November 2026

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