Elamur Research⌕
☰
home / authors / Rui Pan

Rui Pan

Rui Pan has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining; often with Hanze Dong, Jipeng Zhang, Shizhe Diao.

2 papers in our library · 2023–2024

OpenAlex · ORCID · h-index 7 · 28 works · 110 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 314 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #4095

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of Illinois Urbana-ChampaignUrbana · United States2024–2026 · 12 paperscurrent🎓Princeton UniversityPrinceton · United States2022–2025 · 6 papers🎓Hong Kong University of Science and TechnologyHong Kong · Hong Kong2022–2024 · 2 papers

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.

 Concepts, shelves and topics

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSafety Research · 1 workSocial Sciences · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20241 paperMitigating the Alignment Tax of RLHF20231 paperRAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

 Papers

The most cited first (OpenAlex and our library).

  1. RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment (2023 · 239 citations)
    Aligning generative foundation models with human preferences usually relies on RLHF with PPO. PPO is unstable and sample-inefficient, and it must keep several large models in memory at once (policy, reference, reward, critic). The authors propose RAFT (Reward rAnked FineTuning), a simpler alternative that repeats…
  2. Mitigating the Alignment Tax of RLHF (2024 · 82 citations)
    RLHF makes LLMs follow human preferences, but it also tends to erode skills learned in pre-training. This loss is called the alignment tax. The authors measured it by aligning OpenLLaMA-3B on the Anthropic helpfulness/harmlessness data with Rejection Sampling Fine-tuning (RSF) and DPO. They then tracked performance…

All works

4 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. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 239 citations
  2. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 82 citations
  3. TheoremLlama: Transforming General-Purpose LLMs into Lean4 ExpertsarXiv:2407.03203 · original ↗ · no summary yetRuida Wang et al.2024 · 50 citations
  4. Entropy-Regularized Process Reward ModelarXiv:2412.11006 · original ↗ · no summary yetHanning Zhang et al.2024 · 17 citations

 Co-authors here

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

Venues

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

 Cited by

Papers of our library cite their works 314 times (of the 141,840 papers whose bibliographies we read); 26 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/rui-pan/