Elamur Research⌕
☰
home / authors / Changjiang Gao

Changjiang Gao

Changjiang Gao has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Shujian Huang, Fei Yuan, Jiajun Chen.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 2 · 22 works · 27 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 14 times in our library · ⭐ Paper Stars ranking: #9532

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

🎓Nanjing UniversityNanjing · China2023–2026 · 20 paperscurrent🎓City University of Hong KongHong Kong · China2024–2026 · 3 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 2 works

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Could Thinking Multilingually Empower LLM Reasoning? (2025 · 10 citations)
    LLMs are usually assumed to reason best in English. Recent evidence shows that some non-English languages can outperform English on reasoning benchmarks. This paper asks how much accuracy could be gained by having a model reason over the same question in many languages and pooling the results.
  2. ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection (2026 · 4 citations)
    Reasoning models are usually post-trained with RL to think in English, even though sampling chains of thought in several languages can yield more varied solutions and higher Pass@k. ExpLang turns the choice of thinking language into an action the model takes itself during RL. The pipeline has three steps:

 Co-authors here

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

 Cited by

Papers of our library cite their works 14 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated

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