Trevor Cohn
Professor

Room 323
Doug McDonnell Building (#167)

Computing and Information Systems
The University of Melbourne
Natural Language Processing group

Ph: +61383441732

Understanding of human language by computers has been a central goal of Artificial Intelligence since its beginnings, with massive potential to improve communication, provide better information access and automate basic human tasks. My research focuses on technologies for automatic processing of human language, with several applications including automatic translation (akin to Google and Bing's translation tools). My core focus is on probabilistic machine learning modelling of language applications, particularly handling uncertain or partly observed data and structured prediction problems.

News

• November 2020: EMNLP 2020 will be run online
• July 2020: My student Nitika Mathur was awarded a best paper at ACL 2020 (honorable mention), for Tangled Up in BLEU - Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics
• October 2019: I am travelling to Hong Kong for EMNLP, to present two papers in the main conference and two workshop papers.
• September 2019: I will serve as PC chair for EMNLP 2020, alongside Yang Liu and Yulan He.
• July 2019: The group has papers at ICML, WWW, NAACL, ICASSP and ACL (x3).
• July 2018: We hosted ACL 2018 in Melbourne, with Tim Baldwin, Karin Verspoor and myself serving as the local chairs.

Recent Papers

• Xudong Han, Timothy Baldwin and Trevor Cohn (2021). Decoupling Adversarial Training for Fair NLP. In Findings of ACL 2021 (short).
• Jun Wang, Chang Xu, Francisco Guzman, Ahmed El-Kishky, Yuqing Tang, Benjamin Rubinstein and Trevor Cohn (2021). Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. In Findings of ACL 2021.
• Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin Rubinstein and Trevor Cohn (2021). As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. In Findings of ACL 2021 (short).
• Fan Jiang and Trevor Cohn (2021). Incorporating Syntax and Semantics in Coreference Resolution with Heterogeneous Graph Attention Network. In NAACL 2021 (short).
• Shima Khanehzar, Trevor Cohn, Gosia Mikolajczak, Andrew Turpin and Lea Frermann (2021). Framing Unpacked: A Semi-Supervised Interpretable Multi-View Model of Media Frames. In NAACL 2021.
• Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzm'an, Benjamin Rubinstein and Trevor Cohn (2021). Targeted Poisoning Attacks on Black-Box Neural Machine Translation. In WWW 2021.
• Kemal Kurniawan, Lea Frermann, Philip Schulz and Trevor Cohn (2021). PPT: Parsimonious Parser Transfer for Unsupervised Cross-lingual Transfer. In EACL 2021.
• Xudong Han, Timothy Baldwin and Trevor Cohn (2021). Diverse Adversaries for Mitigating Bias in Training. In EACL 2021.
• Philip Arthur, Trevor Cohn and Gholamreza Haffari (2021). Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning. In EACL 2021.