Elamur Research⌕
☰
home / authors / Yifeng Liu

Yifeng Liu

Yifeng Liu has 2 papers in our library, in 2025–2026, most of them on Machine translation, Multilingual & cross-lingual NLP, Low-resource languages; often with Jiajun Chen, Lei Li, Shuaijie She.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 4 · 12 works · 60 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 437 times in our library · ⭐ Paper Stars ranking: #9107

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

🏥Shenzhen Nanshan Center for Chronic Disease ControlShenzhen · China2022–2026 · 13 paperscurrent

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.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 4Research subjects and languages the work is about.Reasoning · 1 workLow-resource languages · 1 workMachine translation · 1 workMultilingual & cross-lingual NLP · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. R-PRM: Reasoning-Driven Process Reward Modeling (2025 · 18 citations)
    Process Reward Models (PRMs) score each step of an LLM's mathematical reasoning. Most existing PRMs output a score directly, which limits how well they learn and gives no explanation for a judgment. Step-level labeled data is also scarce. R-PRM addresses this by having the reward model write an analysis of each step…
  2. Mending the Holes: Mitigating Reward Hacking in Reinforcement Learning for Multilingual Translation (2026 · 2 citations)
    LLM translation quality drops sharply for low-resource languages, and the usual post-training fixes require parallel or preference data that these languages often lack.

 Co-authors here

6 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 437 times (of the 149,439 papers whose bibliographies we read); 138 citing papers with a page here →.

Updated

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