About

I am a researcher at Cohere and a final-year PhD student with the UCL NLP group under the supervision of Pontus Stenetorp and Sebastian Riedel. I have a Masters degree from the UCL Department of Computer Science and a Bachelors in Mechanical Engineering from the University of Malta.

The focus of my current research lies at the intersection of model robustness and dynamic adversarial data collection. I also lead the MSIN0221 Natural Language Processing module at the UCL SoM, and work closely with industry on the application of cutting-edge NLP research. Previously, I have interned at DeepMind with Po-Sen Huang and Johannes Welbl. I have also collaborated with Facebook AI Research (FAIR) under the guidance of Douwe Kiela and Robin Jia on dynamic adversarial data collection, improving model robustness and using generative assistants to improve annotation. I also worked as a Machine Learning Engineer at Bloomsbury AI.

News

13/03/2023	That’s a wrap! Another year of the MSIN0221 Natural Language Processing lectures comes to an end. Exciting to see the growing interest in NLP and its application!
13/03/2023	Gave an invited talk on Dynamic Advsersarial Data Collection for Large Language Models at the UCL AI Centre seminar on The Present and Future of Large Language Models in Theory and Practice.
24/11/2022	Presented recent work on DADC and GAAs at the King’s College London Distributed Artificial Intelligence group. Thanks for the insightful discussions!
17/10/2022	Super excited to announce that I have joined Cohere and will be working on making large language models more useful and robust.
10/07/2022	I’m in Seattle for NAACL 2022! I’ll be presenting Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants on Wednesday, 13th July at 10:45 PST. And don’t forget to join us at the DADC workshop on Thursday, 14th July for same amazing keynote talks, a diverse panel, presentations from our Shared Task participants and best paper winners, posters, prizes & much more!
18/05/2022	Our work Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity has been selected as an outstanding paper at ACL 2022!
13/05/2022	Our work Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants has been accepted as an oral presentation at NAACL 2022!
09/05/2022	Excited to announce that I have joined DeepMind as a Research Scientist Intern.
06/04/2022	Gave an invited talk on Dynamic Adversarial Data Collection for Question Answering at the Oracle Labs ML Seminar Series. This was a particularly fun and interactive one, thanks for the invite!
26/03/2022	The call for participation for the Shared Task at the DADC Workshop co-located with NAACL ‘22 in Seattle is now live! We have three fantastic tracks for you to participate in. Sign up here!
25/03/2022	Presented our work on Dynamic Adversarial Data Collection for QA at the University of Oxford.
19/03/2022	Additional resources from our work on Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation at EMNLP 2021 are now available! We are releasing a collection of synthetically-generated adversarial QA pairs and related resources as well as the models used to generate the questions.

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Publications

Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants

Max Bartolo, Tristan Thrush, Sebastian Riedel, Pontus Stenetorp, Robin Jia, Douwe Kiela. In NAACL, 2022.

Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

Yao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel, Pontus Stenetorp. In ACL (outstanding paper), 2022.

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Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality

Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, Candace Ross. In CVPR, 2022.

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Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks

Tristan Thrush, Kushal Tirumala, Anmol Gupta, Max Bartolo, Pedro Rodriguez, Tariq Kane, William Gaviria Rojas, Peter Mattson, Adina Williams, Douwe Kiela. In ACL Demo Track, 2022.

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Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation

Max Bartolo, Tristan Thrush, Robin Jia, Sebastian Riedel, Pontus Stenetorp, Douwe Kiela. In EMNLP, 2021.

Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification

Maximilian Mozes, Max Bartolo, Pontus Stenetorp, Bennett Kleinberg, Lewis D. Griffin. In EMNLP, 2021.

Dynabench: Rethinking Benchmarking in NLP

Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams. In NAACL, 2021.

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