Jianhuang Lai
Jianhuang Lai has 2 papers in our library, in 2018–2019, most of them on Machine translation; often with Lijun Wu, Tao Qin, Tie-Yan Liu.
OpenAlex · ORCID · Wikidata · h-index 64 · 522 works · 15,759 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 142 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4033
Affiliations
🎓Sun Yat-sen UniversityGuangzhou ·
China2004–2026 · 468 papers🔬Guangdong Province Key Laboratory of Information Security TechnologyGuangzhou ·
China2006–2026 · 153 papers🏛️Ministry of Education of the People's Republic of ChinaBeijing ·
China2017–2026 · 28 papers🎓Guangdong Polytechnic Normal UniversityGuangzhou ·
China2026 · 1 paper🔬National Supercomputer Center in GuangzhouGuangzhou ·
China2026 · 1 paper🔬Key Laboratory of Guangdong ProvinceGuangzhou ·
China2008–2022 · 18 papers🔬SYSU-CMU International Joint Research InstituteShunde ·
China2014–2015 · 9 papers🔬Guangdong Province Key Laboratory of Computational ScienceGuangzhou ·
China2016–2023 · 8 papers🎓Guangzhou Xinhua UniversityGuangzhou2021–2023 · 8 papers🎓Hong Kong Baptist UniversityHong Kong ·
Hong Kong2002–2004 · 4 papers
Concepts, shelves and topics
📚 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 1Research subjects and languages the work is about.Machine translation · 2 works
Works by year
2010s
20191 paperExploiting Monolingual Data at Scale for Neural Machine Translation20181 paperA Study of Reinforcement Learning for Neural Machine Translation
Papers
- A Study of Reinforcement Learning for Neural Machine Translation (2018 · 234 citations)
Reinforcement learning can align NMT training with sequence-level metrics such as BLEU. In practice it is unstable, and most earlier evidence came from shallow RNN models. Lijun Wu and colleagues ran a systematic study of RL for deep Transformer models on large datasets: WMT14 English-German, WMT17 English-Chinese… - Exploiting Monolingual Data at Scale for Neural Machine Translation (2019 · 102 citations)
Back translation (BT) is a standard way to use target-language monolingual text in neural machine translation.
All works
- A Study of Reinforcement Learning for Neural Machine TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Lijun Wu, Fei Tian, Tao Qin, et al.2018 · 234 citations
- Exploiting Monolingual Data at Scale for Neural Machine TranslationConference on Empirical Methods in Natural Language Processing (EMNLP)Lijun Wu, Yiren Wang, Yingce Xia, et al.2019 · 102 citations
- Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also MatterProceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · original ↗ · no summary yetLijun Wu et al.2018 · 71 citations
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