News
- 21/09/2022:
Yihong will be presenting ReFactorGNNs in ELLIS PhD Symposium 2022. Come to our poster if you are curious about why factorisation-based models are special message-passing GNNs!
- 15/09/2022:
Our paper ReFactorGNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective has been accepted by NeurIPS 2022! Congrats Yihong, Pushkar, Luca, Pasquale, Pontus and Sebastian!
- 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!
- 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!
- 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.
- 28/02/2022:
Our AAAI 2022 tutorial, On Explainable AI: From Theory to Motivation, Industrial Applications, XAI Coding & Engineering Practices, was an outstanding success, with more than 600 attendees – check it out! Congratulations Pasquale and collaborators!
- 20/01/2022:
AdversarialQA is currently the 3rd most downloaded QA dataset on Huggingface 🤗 Datasets right after the benchmark SQuADv1.1 and SQuADv2!
People

Sebastian Riedel
Professor

Pontus Stenetorp
Associate Professor

Tim Rocktäschel
Affiliated Faculty (Associate Professor)

Ed Grefenstette
Honorary Professor

Pasquale Minervini
Senior Research Fellow, Principal Investigator for H2020 CLARIFY

Luca Franceschi
Research Fellow

Oana-Maria Camburu
Research Fellow
Linqing Liu
PhD Student

Max Bartolo
PhD Student

Maximilian Mozes
PhD Student

Mikayel Samvelyan
PhD Student

Minqi Jiang
PhD student

Patrick Lewis
PhD Student

Sohee Yang
PhD student

Tom Crossland
PhD Student

Yao Lu
PhD Student

Yihong Chen
PhD Student

Yuxiang Wu
PhD Student

Zhengyao Jiang
PhD Student

Alice Winters
Group Administrator
Alumni

Matko Bošnjak
Now a Research Scientist at DeepMind

Alastair Roberts
Alastair’s interests lie in natural language processing & machine learning.

Johannes Welbl
Now a Research Scientist at DeepMind

Luke Hewitt
Now a PhD student at MIT

Gerasimos Lampouras
Now a research associate at University of Sheffield

Saku Sugawara
Now back to being a Ph.D. student at the University of Tokyo.

Sonse Shimaoka
Now a master student at Tohoku University

Zhao Zhang
Now back to being a PhD student at the Chinese Academy of Sciences.

Andreas Vlachos
Now a senior lecturer at University of Cambridge

Guillaume Bouchard
Now CEO at CheckStep

Thomas Demeester
Now a post-doc at University of Ghent

Jason Naradowsky
Now a research scientist at Preferred Networks (PFN)

Théo Trouillon
Now back to being a PhD student at Xerox Research Centre Europe

Marzieh Saeidi
Now a Research Scientist at Facebook

Isabelle Augenstein
Now an associate professor at University of Copenhagen

Naoya Inoue
Now an assistant professor at Tohoku University

Tim Dettmers
Now a PhD student at University of Washington

V. Ivan Sanchez
Now an NLP researcher at Lenovo

Andres Campero
Now back to being a PhD student at MIT

Takuma Yoneda
Now a student at Toyota Technological Institute at Chicago

Georgios Spithourakis
Now a ML engineer at PolyAI
Publications
Datasets
SynQA
A synthetic dataset of 315k QA pairs on passages from SQuAD designed to help make QA models more robust to human adversaries. This resource is also available in HuggingFace datasets at https://huggingface.co/datasets/mbartolo/synQA.
AdversarialQA (from Beat the AI)
A dataset of 36k challenging extractive QA pairs consisting of training, evaluation and test data collected using three different models-in-the-loop: BiDAF, BERT and RoBERTa.
KILT: a Benchmark for Knowledge Intensive Language Tasks
A resource for training, evaluating and analyzing NLP models on Knowledge Intensive Language Tasks. KILT has been built from 11 datasets representing 5 tasks.
MLQA
A multi-way aligned extractive QA evaluation benchmark MLQA contains QA instances in 7 languages, English, Arabic, German, Spanish, Hindi, Vietnamese and Simplified Chinese.
ShARC: Shaping Answers with Rules through Conversation
A collection of 32k task instances based on real-world rules and crowd-generated questions and scenarios requiring both the interpretation of rules and the application of background knowledge.
WikiHop & MedHop (QAngaroo)
Multi-hop question answering datasets from two different domains, designed to enabe models to combine disjoint pieces of textual evidence.