Pinzhen Chen

I am a postdoctoral researcher in School of Informatics, University of Edinburgh, where I am also a member of the machine translation group, EdinburghNLP, and Institute for Language, Cognition and Computation. I also go by Patrick or 陈品桢.

I work on the High Performance Language Technologies project, specifically on the translation system pipeline and multilingual large language models (LLMs). I occasionally contribute to MaLA and UTTER on LLM multilinguality and evaluation. I am also a senior NLP engineer at Aveni.ai, building LLMs for financial services.

Last updated on 14 Dec 2024. [ | Semantic Scholar | Google Scholar | GitHub | Hugging Face | LinkedIn]

Experience

• 2024-present, University of Edinburgh, Research Associate
• 2024-present, Aveni.ai, Senior NLP Engineer
• 2020-2024, University of Edinburgh, PhD supervised by Kenneth Heafield and Barry Haddow
• 2023, Microsoft Research Asia, Research Visit
• 2022, Huawei Noah's Ark Lab, Research Scientist Intern
• 2019, University of Edinburgh, Research Assistant
• 2015-2019, University of Edinburgh, BEng Artificial Intelligence and Software Engineering. Awarded first class honours and a Class Medal for attaining the top performance in the degree
• 2018, Goldman Sachs, Technology Analyst Intern

Services

• Action Editor/Area Chair
  • Association for Computational Linguistics Rolling Review (ARR): 2024
• Program Committee/Reviewer
  • International Conference on Learning Representations (ICLR): 2025
  • Conference on Neural Information Processing Systems (NeurIPS): 2024
  • ACM Computing Surveys: 2024
  • Information Processing and Management: 2024
  • Conference on Language Modeling (COLM): 2024
  • European Conference on Artificial Intelligence (ECAI): 2024
  • Association for Computational Linguistics Rolling Review (ARR): 2021, 2023, 2024
  • Joint Conference on Lexical and Computational Semantics (*SEM): 2022, 2023, 2024
  • Financial Support for Third Parties from the Horizon Europe project Unified Transcription and Translation for Extended Reality (UTTER FSTP): 2023
  • Workshop on Instruction Tuning and Instruction Following: 2023
  • Conference on Empirical Methods in Natural Language Processing (EMNLP): 2023
  • Conference on Machine Translation (WMT): 2021, 2022
  • International Workshop on Semantic Evaluation (SemEval): 2022
• Teaching Assistant at University of Edinburgh
  • Machine Learning Practical: mentor and marker, 2020-21, 2021-22, 2022-23
  • Introductory Applied Machine Learning: marker, 2020-21, 2021-22
  • Informatics Research Proposal: tutor, 2020-21
  • System Design Project: mentor, 2018-19
• Supervision
  • Dayyán O'Brien. 2024. Research Intern. Multilingual data processing, as part of the EMMA-500 model's effort.
  • Zhanghao Hu, Yijun Yang, and Junjie Xu. 2023. Machine Learning Pratical project on efficient question answering, shortlisted for a best project prize donated by IBM UK and published at LREC-COLING 2024.

Research

Multilingualism

• Shaoxiong Ji* and Pinzhen Chen*. How many languages make good multilingual instruction tuning? A case study on BLOOM. 2025. Accepted to the 31st International Conference on Computational Linguistics.
• Shaoxiong Ji, Zihao Li, Indraneil Paul, Jaakko Paavola, Peiqin Lin, Pinzhen Chen, Dayyán O'Brien, Hengyu Luo, Hinrich Schütze, Jörg Tiedemann, and Barry Haddow. EMMA-500: Enhancing massively multilingual adaptation of large language models. 2024. arXiv preprint.
• Pinzhen Chen, Simon Yu, Zhicheng Guo, and Barry Haddow. Is it good data for multilingual instruction tuning or just bad multilingual evaluation for large language models?. 2024. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing.
• Nikolay Arefyev, Mikko Aulamo, Pinzhen Chen, Ona de Gibert, Barry Haddow, Jindřich Helcl, Bhavitvya Malik, Gema Ramírez-Sánchez, Pavel Stepachev, Jörg Tiedemann, Dušan Variš, and Jaume Zaragoza. HPLT's first release of data and models. 2024. In Proceedings of the 25th Annual Conference of the European Association for Machine Translation.
• Nikolay Bogoychev, Pinzhen Chen, Barry Haddow, and Alexandra Birch. The ups and downs of large language model inference with vocabulary trimming by language heuristics. 2024. In Proceedings of the Fifth Workshop on Insights from Negative Results in NLP.
• Pinzhen Chen*, Shaoxiong Ji*, Nikolay Bogoychev, Andrey Kutuzov, Barry Haddow, and Kenneth Heafield. Monolingual or multilingual instruction tuning: Which makes a better Alpaca. 2024. In Findings of the Association for Computational Linguistics: EACL 2024.
• Ashok Urlana*, Pinzhen Chen*, Zheng Zhao, Shay B. Cohen, Manish Shrivastava, and Barry Haddow. PMIndiaSum: Multilingual and cross-lingual headline summarization for languages in India. 2023. In Findings of the Association for Computational Linguistics: EMNLP 2023.

Translation

• Dawei Zhu, Pinzhen Chen, Miaoran Zhang, Barry Haddow, Xiaoyu Shen, and Dietrich Klakow. Fine-tuning large language models to translate: Will a touch of noisy data in misaligned languages suffice?. 2024. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing.
• Vilém Zouhar*, Pinzhen Chen*, Tsz Kin Lam, Nikita Moghe, and Barry Haddow. Pitfalls and outlooks in using COMET. 2024. In Proceedings of the Ninth Conference on Machine Translation.
• Vivek Iyer, Bhavitvya Malik*, Pavel Stepachev*, Pinzhen Chen, Barry Haddow, and Alexandra Birch. Quality or quantity? On data scale and diversity in adapting large language models for low-resource translation. 2024. In Proceedings of the Ninth Conference on Machine Translation.
• Pinzhen Chen, Zhicheng Guo, Barry Haddow, and Kenneth Heafield. Iterative translation refinement with large language models. 2024. In Proceedings of the 25th Annual Conference of the European Association for Machine Translation.
• Nikolay Bogoychev* and Pinzhen Chen*. Terminology-aware translation with constrained decoding and large language model prompting. 2023. In Proceedings of the Eighth Conference on Machine Translation.
• Vivek Iyer, Pinzhen Chen, and Alexandra Birch. Towards effective disambiguation for machine translation with large language models. 2023. In Proceedings of the Eighth Conference on Machine Translation.
• Nikolay Bogoychev* and Pinzhen Chen*. The highs and lows of simple lexical domain adaptation approaches for neural machine translation. 2021. In Proceedings of the Second Workshop on Insights from Negative Results in NLP.
• Pinzhen Chen*, Nikolay Bogoychev*, Kenneth Heafield, and Faheem Kirefu. Parallel sentence mining by constrained decoding. 2020. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.
• Marta Bañón, Pinzhen Chen, Barry Haddow, Kenneth Heafield, Hieu Hoang, Miquel Esplà-Gomis, Mikel L. Forcada, Amir Kamran, Faheem Kirefu, Philipp Koehn, Sergio Ortiz Rojas, Leopoldo Pla Sempere, Gema Ramírez-Sánchez, Elsa Sarrías, Marek Strelec, Brian Thompson, William Waites, Dion Wiggins, and Jaume Zaragoza. ParaCrawl: Web-scale acquisition of parallel corpora. 2020. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.

Other topics

• Mateusz Klimaszewski, Pinzhen Chen, Liane Guillou, Ioannis Papaioannou, Barry Haddow, and Alexandra Birch. AveniBench: Accessible and versatile evaluation of finance intelligence. 2025. Accepted to the Joint Workshop of the 9th Financial Technology and Natural Language Processing, the 6th Financial Narrative Processing, and the 1st Workshop on Large Language Models for Finance and Legal.
• Hanxu Hu*, Simon Yu*, Pinzhen Chen*, and Edoardo M. Ponti. Fine-tuning large language models with sequential instructions. 2024. arXiv preprint.
• Yuanchao Li, Pinzhen Chen, Peter Bell, and Catherine Lai. Crossmodal ASR error correction with discrete speech units. 2024. Accepted to 2024 IEEE Spoken Language Technology Workshop.
• Zhanghao Hu*, Yijun Yang*, Junjie Xu*, Yifu Qiu, and Pinzhen Chen. EEE-QA: Exploring effective and efficient question-answer representations. 2024. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation.
• Zeyu Zhao, Pinzhen Chen, and Peter Bell. Regarding topology and adaptability in differentiable WFST-based E2E ASR. 2024. In 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops.
• Pinzhen Chen and Gerasimos Lampouras. Exploring data augmentation for code generation tasks. 2023. In Findings of the Association for Computational Linguistics: EACL 2023.
• Pinzhen Chen and Zheng Zhao. A unified model for reverse dictionary and definition modelling. 2022. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing.
• Pinzhen Chen and Kenneth Heafield. Approaching neural Chinese word segmentation as a low-resource machine translation task. 2022. In Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation.

Personal

I enjoy travelling, cooking, and doing photography. I sometimes play badminton, basketball, as well as board and card games. Thanks for reading this far. Here is the reward for reinforcement—photos of my cat Luckie.