Josef Valvoda
I am a final-year PhD student at the University of Cambridge supervised by Professor Simone Teufel (Cambridge) and Professor Ryan Cotterell (ETH). Before joining the Natural Language and Information Processing group I’ve completed the MPhil in Advanced Computer Science also at the University of Cambridge. Before that, I’ve obtained a Bachelor of Law at the University of Exeter. I’m a member of Rycolab at ETH Zurich and fully funded by the Huawei Reseach Scholarship.
My PhD work focuses on Aritifical Intelligence and Law. I belive that automation is the key for widening access to justice. I think about what deep learning models can learn, have learned and should learn. I’m on the program committee of the Competition on Legal Information Extraction/Entailment (COLIEE), Natural Legal Language Processing Workshop (NLLP) and the International Workshop on Juris-informatics (JURISIN).
While Legal NLP is the focus of my thesis, I am also very much interested in broader NLP research. I have recently published work on testing the compositional behaviour of neural networks. Finally, I continue to collaborate on developing (probing) methods that could better our understanding of what the neural models learn.
Outside of my work in Cambridge, I’ve been frequenting Japan’s National Institute of Informatics (NII), worked with startups (TechWolf) and interned as AI/ML researcher at Apple and Applied Scientist at Amazon.
You can find me on: Twitter, GitHub, LinkedIn or the department website. PDF copy of my CV is here.
selected publications
- TACLOn the Role of Negative Precedent in Legal Outcome PredictionTransactions of the Association for Computational Linguistics 2023
- COLINGBenchmarking Compositionality with Formal LanguagesIn Proceedings of the 29th International Conference on Computational Linguistics 2022
- NAACLWhat About the Precedent: An Information-Theoretic Analysis of Common LawIn Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies 2021
- ACLInformation-Theoretic Probing for Linguistic StructureIn Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020 2020