🧑‍🔬 Lei Liu

🏛️ Affiliations

🏢Ant GroupHangzhou · China2021–2026 · 14 paperscurrent🎓Zhejiang UniversityHangzhou · China2026 · 5 paperscurrent🎓Chinese University of Hong Kong, ShenzhenShenzhen · China2020–2025 · 14 papersEmployment · SSEEducation 2020–2025 · doctor, science and engineering🎓The Hong Kong University of Science and Technology (Guangzhou)Guangzhou · China2023–2025 · 7 papers🎓Shenzhen Research Institute of Big DataShenzhen · China2020–2024 · 6 papers🎓Chinese University of Hong KongHong Kong · China2022–2023 · 3 papers🎓Wuhan University of Science and TechnologyWuhan · China2014–2018Education 2014–2018 · Bachelor, computer science

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution 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. Artificial Intelligence Bias on English Language Learners in Automatic Scoring (2025 · 15 citations)
   The paper asks whether automatic scoring of short written science answers treats English Language Learners (ELLs) unfairly, and in particular whether ELLs being underrepresented in training data is the cause.
2. BRIDGE the Gap: Mitigating Bias Amplification in Automated Scoring of English Language Learners via Inter-group Data Augmentation (2026)
   Automated scorers for student answers, built on deep models and LLMs, can widen score gaps between student groups beyond the gaps in the human labels they learn from.
3. ClinAlign: Scaling Healthcare Alignment from Clinician Preference (2026)
   Medical LLMs score well on exam-style tests, but their free-form answers often miss what clinicians actually expect.
4. GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMs (2026)
   LLM rerankers face a trade-off between accuracy and speed. Pointwise scoring is fast but never compares documents with each other. Listwise ranking does compare them, but it exceeds context limits and relies on slow sequential sliding windows. GroupRank takes a middle path: it splits the candidate pool into small…
5. Perplexity-Aware Data Scaling Law: Perplexity Landscapes Predict Performance for Continual Pre-training (2026)
   Continual pre-training (CPT) adapts general LLMs to specialised domains such as medicine. Simply adding more domain tokens quickly stops paying off, because classical scaling laws treat every token as equally useful. This paper proposes a perplexity-aware data scaling law. The frozen base model runs one forward pass…

🤝 Co-authors here

12 of 22 co-authors with a page, the most papers together first.

• Yue Shen ×3
• Hao Zhu ×2
• Jian Wang ×2
• Jinjie Gu ×2
• Ninghao Liu ×2
• Xiaoming Zhai ×2
• Xuansheng Wu ×2
• Yun Wang ×2
• Benyou Wang
• Binbin Hu
• Dan Yang
• Duolin Sun

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 ×2: Findings of the Association for Computational Linguistics 2026 ×2
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
• Lecture notes in computer science: Lecture notes in computer science 2025

🔗 Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated 1 November 2026

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