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Chonghua Liao

Chonghua Liao has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Angang Du, Bofei Gao, Bowei Xing.

2 papers in our library · 2025–2026

OpenAlex · h-index 3 · 15 works · 26 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 450 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #4128

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

🎓Tsinghua UniversityBeijing · China2021–2026 · 15 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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workMathematics · 1 work

🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Kimi k1.5: Scaling Reinforcement Learning with LLMs (2025 · 431 citations)
    Next-token pretraining is limited by how much high-quality text exists. The Kimi Team proposes reinforcement learning as another way to keep scaling: the model creates its own training signal by exploring solutions and receiving rewards. The report describes how they built Kimi k1.5, a multimodal LLM. Training runs…
  2. TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning (2026 · 8 citations)
    RL methods such as GRPO strengthen LLM reasoning, but they learn only from rollouts the model samples freely from its own distribution.

All works

5 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. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  2. FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding ↗Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYanan Zheng et al.2022 · 34 citations
  3. TemplateRL: Structured Template-Guided Reinforcement Learning for LLM ReasoningFindings of the Association for Computational LinguisticsJinyang Wu, Chonghua Liao, Mingkuan Feng, et al.2026 · 8 citations
  4. Zero-Label Prompt Selection ↗arXiv (Cornell University) · no summary yetChonghua Liao, Yanan Zheng, Zhilin Yang2022 · 7 citations
  5. Beyond Examples: Towards Automated Thought-level In-Context Reasoning for Large Language Models ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetJinyang Wu et al.2026

 Co-authors here

12 of 16 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 450 times (of the 149,439 papers whose bibliographies we read); 140 citing papers with a page here →.

Updated

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