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Peiquan Jin

Peiquan Jin has 3 papers in our library, in 2026, most of them on Efficient models & compression, Language models & pretraining; often with Li Ni, Lin Mu, Yiwen Zhang.

3 papers in our library · 2026

OpenAlex · ORCID · Wikidata · h-index 21 · 324 works · 2,082 citations OpenAlex, 2026-10-14

📄 3 works in our library · ⭐ Paper Stars ranking: #11392

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

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. Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions (2026 · 1 citation)
    LoRA, the standard parameter-efficient method for fine-tuning LLMs, builds each weight update as a product of two low-rank matrices.
  2. GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model Recommendation (2026)
    LLM-based recommenders have trouble combining a language model's textual knowledge with collaborative signals from user–item interactions, which are naturally graph-shaped.
  3. TalkLoRA: Communication-Aware Mixture of Low-Rank Adaptation for Large Language Models (2026)
    Mixture-of-Experts variants of LoRA (MoELoRA) split adaptation across several low-rank experts, but each expert works in isolation.

 Co-authors here

5 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.

Updated

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