Pinzhen Chen
I am a postdoctoral researcher in School of Informatics, University of Edinburgh. I am a member of the
large
machine translation group,
EdinburghNLP,
and Institute for Language, Cognition and
Computation.
I work on the
High Performance Language Technologies project:
translation system pipeline, data cleaning, evaluation, and model deliverables
LLM instruction tuning: multilinguality, reasoning, and alignment
and occasionally contribute to UTTER on multilinguality and
multi-cultrual evaluation.
I also go by Patrick or 陈品桢. Last updated on 21 June 2024.
[pinzhen.chen@ed.ac.uk
| Semantic Scholar
| Google Scholar
| GitHub
| Hugging Face
| LinkedIn]
Experience
- 2024-present, University of Edinburgh, Research Associate
- 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
- Program Committee/Reviewer
- 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
- NeurIPS 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. Research Intern.
- Zhanghao Hu, Yijun Yang, Junjie Xu. Machine Learning Pratical project, shortlisted for a best
project prize donated by IBM UK and published at LREC-COLING 2024.
Research
- Large language models for multilingualism, translation, and reasoning
-
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.
arXiv preprint.
-
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.
Accepted to the 25th Annual Conference of the European Association for Machine
Translation.
[.pdf
| code
| data and models
| website]
-
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.
arXiv preprint.
-
Hanxu Hu*, Simon Yu*, Pinzhen Chen*, and Edoardo M. Ponti.
Fine-tuning large language models with
sequential instructions. 2024.
arXiv preprint.
-
Shaoxiong Ji and Pinzhen Chen.
Lucky 52: How many languages are needed
to instruction fine-tune large language models?. 2024.
arXiv preprint.
-
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.
[.pdf
| .bib
| data
| code
| models]
-
Pinzhen Chen, Zhicheng Guo, Barry Haddow, and Kenneth Heafield.
Iterative translation refinement with
large language models. 2024.
Accepted to 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.
[.pdf
| .bib
| poster]
-
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.
[.pdf
| .bib
| data]
- Modelling: speech-text, efficiency, debiasing
-
Yuanchao Li, Pinzhen Chen, Peter Bell, and Catherine Lai.
Crossmodal ASR error correction with
discrete speech units. 2024.
arXiv preprint.
-
Zeyu Zhao, Pinzhen Chen, and Peter Bell.
Regarding topology and adaptability in
differentiable WFST-based E2E ASR. 2024.
Accepted to ICASSP 2024 Workshop on Explainable AI for Speech and Audio.
-
Yijun Yang, Jie He, Pinzhen Chen, Victor Gutierrez Basulto, and Jeff Pan.
UniArk: Improving
generalisation and consistency for factual knowledge extraction through debiasing. 2024.
In Proceedings of the 2024 Conference of the North American Chapter of the Association for
Computational Linguistics: Human Language Technologies.
[.pdf
| .bib
| code and data]
-
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.
[.pdf
| .bib
| code]
-
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.
[.pdf
| .bib
| best paper award]
- Generative retrieval, word-definition retrieval
- Language generation, translation, summarization
-
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.
[.pdf
| .bib
| poster
| code
| data]
-
Pinzhen Chen and Gerasimos Lampouras.
Exploring data
augmentation for code generation tasks. 2023.
In Findings of the Association for Computational Linguistics: EACL 2023.
[.pdf
| .bib
| poster
| talk]
-
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.
[.pdf
| .bib
| best paper award out of 94]
-
Zheng Zhao and Pinzhen Chen.
To adapt or to fine-tune: A case
study on abstractive summarization. 2022.
In Proceedings of the 21st Chinese National Conference on Computational Linguistics.
[.pdf
| .bib
| poster
| code]
-
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.
[.pdf
| .bib
| talk
| website]
- Building competitive translation systems
- Theses
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.
