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

• 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.

• Najam Zaidi, Trevor Cohn and Gholamreza Haffari (2020). Decoding As Dynamic Programming For Recurrent Autoregressive Models. In ICLR 2020.
• Dat Nguyen, Zenan Zhai, Hiyori Yoshikawa, Biaoyan Fang, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Saber Akhondi, Trevor Cohn, Timothy Baldwin and Karin Verspoor (2020). ChEMU: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents. In ECIR 2020.
• Jiayuan He, Dat Nguyen, Saber Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Jingqi Wang, Yuankai Ren, Zhi Zhang, Yaoyun Zhang, Mai Dao, Pedro Ruas, Andre Lamurias, Francisco Couto, Jenny Copara, Nona Naderi, Julien Knafou, Patrick Ruch, Douglas Teodoro, Daniel Lowe, John Mayfield, Abdullatif K"oksal, Hilal D"onmez, Elif "Ozkirimli, Arzucan "Ozg"ur, Darshini Mahendran, Gabrielle Gurdin, Nastassja Lewinski, Christina Tang, Bridget McInnes, C. Malarkodi, Pattabhi Rao, Sobha Devi, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin and Karin Verspoor (2020). An Extended Overview of the CLEF 2020 ChEMU Lab: Information Extraction of Chemical Reactions from Patents. In Working Notes of CLEF 2020 - Conference and Labs of the Evaluation Forum.
• Jiayuan He, Dat Nguyen, Saber Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin and Karin Verspoor (2020). Overview of ChEMU 2020: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents. In CLEF 2020.
• Nitika Mathur, Timothy Baldwin and Trevor Cohn (2020). Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics. In ACL 2020.