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Juhao Liang

Juhao Liang has 2 papers in our library, in 2023–2024, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Semitic languages; often with Bang An, Benyou Wang, Chen Zhang.

2 papers in our library · 2023–2024

OpenAlex · h-index 2 · 9 works · 25 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 71 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5189

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

🎓Chinese University of Hong Kong, ShenzhenShenzhen · China2023–2026 · 5 paperscurrent🎓Shenzhen Research Institute of Big DataShenzhen · China2023–2025 · 4 papers🎓Chinese University of Hong KongHong Kong · Hong Kong2023–2025 · 3 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 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 3Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 1 workLanguage models & pretraining · 1 workSemitic languages · 1 work

 Works by year

2020s

20241 paperAlignment at Pre-training! Towards Native Alignment for Arabic LLMs20231 paperPhoenix: Democratizing ChatGPT across Languages

 Papers

The most cited first (OpenAlex and our library).

  1. Phoenix: Democratizing ChatGPT across Languages (2023 · 68 citations)
    Open ChatGPT-style assistants released in early 2023 were mostly built for English, or English plus Chinese.
  2. Alignment at Pre-training! Towards Native Alignment for Arabic LLMs (2024 · 14 citations)
    Most LLM alignment work happens after pre-training, through instruction tuning or reinforcement learning from feedback. The authors ask whether alignment can start earlier, inside the pre-training corpus itself. They call this "native alignment" and test it on Arabic. Their pipeline has four steps:

All works

3 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. Phoenix: Democratizing ChatGPT across LanguagesarXiv:2304.10453Zhihong Chen, Feng Jiang, Junying Chen, et al.2023 · 68 citations
  2. Alignment at Pre-training! Towards Native Alignment for Arabic LLMsConference on Neural Information Processing Systems (NeurIPS)Juhao Liang, Zhenyang Cai, Jianqing Zhu, et al.2024 · 14 citations
  3. Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary ExpansionProceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · original ↗ · no summary yetJianqing Zhu et al.2025 · 11 citations

 Co-authors here

12 of 17 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 71 times (of the 141,840 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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