Our group is part of the UCL Computer Science department, affiliated with CSML and based at 90, High Holborn, London. We also organise the South England Natural Language Processing Meetup. Get in touch if you're interested in attending.If you are interested in doing a PhD with us, please have a look at these instructions.

News

  • 16/10/2019:

    We're releasing a new cross-lingual Question Answering dataset, MLQA: Evaluating Cross-lingual Extractive Question Answering Check out the dataset here

  • 03/09/2019:

    Language Models as Knowledgebases? accepted at EMNLP 2019! Code for the paper's experiments, and the LAMA probe are available here

  • 13/06/2019:

    Unsupervised Question Answering by Cloze Translation accepted at ACL 2019! Code and synthetic training data will be available here

  • 13/06/2019:

    NLProlog: Reasoning with Weak Unification for Question Answering in Natural Language accepted at ACL 2019! Code and synthetic training data is available here

  • 28/09/2018:

    Interpretation of Natural Language Rules in Conversational Machine Reading accepted at EMNLP 2018 - CodaLab challenge are now LIVE at sharc-data.github.io!

  • 26/09/2018:

    Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection accepted at EMNLP 2018 - code available at this link!

  • 22/08/2018:

    Cape achieves new SoTA on the TriviaQA Wiki dataset codalab Leaderboard. More details can be found here. Cape is super easy to use, extend and integrate into all kinds of software!

News Archive →

People

Sebastian Riedel

Sebastian Riedel

Professor

Sebastian Riedel

Sebastian works in NLP and Machine Learning. He is particularly interested in helping machines to read more accurately by leveraging...

Pontus Stenetorp

Pontus Stenetorp

Lecturer

Pontus Stenetorp

Pontus works somewhere in the intersection between Natural Language Processing and Machine Learning. He is particularly interested in...

Tim Rocktäschel

Tim Rocktäschel

Lecturer

Tim Rocktäschel

Reinforcement Learning – Deep Learning – Natural Language Processing

Tim's research focuses on sample-efficient and more...

Ed Grefenstette

Ed Grefenstette

Honorary Reader

Ed Grefenstette

Ed is interesting in teaching machines to understand and communicate using language (formal and natural), and in both neural and symbolic...

Pasquale Minervini

Pasquale Minervini

Senior Research Associate

Pasquale Minervini

Pasquale is interested in Machine Reading, and how to leverage background knowledge in representation learning algorithms. He is currently...

Matko Bošnjak

Matko Bošnjak

Final Year PhD Student

Matko Bošnjak

Matko's interests include both natural and unnatural language processing, and their interplay. Specifically, he's enjoying differentiable...

Johannes Welbl

Johannes Welbl

Final Year PhD Student

Johannes Welbl

Johannes is interested in reading comprehension, dataset assembly, representation learning, and their interplay.

Tom Crossland

Tom Crossland

PhD Student

Tom Crossland

Tom is an astrophysicist working with the MR group and the Mullard Space Science Laboratory, interested in Machine Learning applications to...

Patrick Lewis

Patrick Lewis

1st Year PhD Student

Patrick Lewis

Patrick is a first year PhD student, interested in Transfer Learning, Machine Reading and leveraging world knowledge to improve predictions...

Yuxiang Wu

Yuxiang Wu

1st Year PhD Student

Yuxiang Wu

Yuxiang is a first year PhD student, interested in combining connectionism and symbolism to improve the reasoning capability of NLP systems....

Max Bartolo

Max Bartolo

PhD Student

Max Bartolo

Max's current research focuses on natural language processing, with particular interest in question answering and machine reasoning.

Minqi Jiang

Minqi Jiang

PhD student

Minqi Jiang

Minqi studies how decision-making agents can make use of compositional structures, like language, to learn more generalizable behaviors.

Yihong Chen

Yihong Chen

1st Year PhD Student

Yihong Chen

Yihong is interested in almost everything, currently working on methods that empower efficient learning of symbols. Welcome any messages...

Alastair Roberts

Alastair Roberts

Visiting Researcher

Alastair Roberts

Alastair's interests lie in natural language processing & machine learning. His current work is focused on question answering.

Zhao Zhang

Zhao Zhang

Visiting PhD Student

Zhao Zhang

Zhao is a visiting PhD student from the Institute of Computing Technology, Chinese Academy of Sciences, interested in knowledge graphs.

MSc Students

Zhengyao Jiang

Zhengyao Jiang

Mres Computational Statistics and Machine Learning

Zhengyao Jiang

Zhengyao is interested in topics about reinforcement leanring, relational inductive bias, and bridging symbolic reasoning and deep learning....

Alumni

Andreas Vlachos

Andreas Vlachos

Now a senior lecturer at University of Cambridge

Andreas Vlachos

Former Research Associate

Luke Hewitt

Luke Hewitt

Now a PhD student at MIT

Luke Hewitt

Former Intern

Gerasimos Lampouras

Gerasimos Lampouras

Now a research associate at University of Sheffield

Gerasimos Lampouras

Former Research Associate

Saku Sugawara

Saku Sugawara

Saku is a Ph.D. student at the University of Tokyo, interested in natural language understanding by machines.

Saku Sugawara

Former Visiting PhD Student

Sonse Shimaoka

Sonse Shimaoka

Now a master student at Tohoku University

Sonse Shimaoka

Former Intern

Guillaume Bouchard

Guillaume Bouchard

Now a Research Manager at Facebook

Guillaume Bouchard

Former Senior Research Associate

Thomas Demeester

Thomas Demeester

Now a post-doc at University of Ghent

Thomas Demeester

Former Visiting Researcher

Jason Naradowsky

Jason Naradowsky

Now a research scientist at Preferred Networks (PFN)

Jason Naradowsky

Former Research Associate

Théo Trouillon

Théo Trouillon

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

Théo Trouillon

Former Visiting PhD Student

Marzieh Saeidi

Marzieh Saeidi

Now a Research Scientist at Facebook

Marzieh Saeidi

Former PhD Student

Isabelle Augenstein

Isabelle Augenstein

Now an assistant professor at University of Copenhagen

Isabelle Augenstein

Former Research Associate

Naoya Inoue

Naoya Inoue

Now an assistant professor at Tohoku University

Naoya Inoue

Former Visiting Researcher

Tim Dettmers

Tim Dettmers

Now a PhD student at University of Washington

Tim Dettmers

Former Intern

V. Ivan Sanchez

V. Ivan Sanchez

Now an NLP researcher at Lenovo

V. Ivan Sanchez

Former PhD Student

Andres Campero

Andres Campero

Now back to being a PhD student at MIT

Andres Campero

Former Visiting PhD Student

Takuma Yoneda

Takuma Yoneda

Now a student at Toyota Technological Institute at Chicago

Takuma Yoneda

Former Intern

Georgios Spithourakis

Georgios Spithourakis

Now a ML engineer at PolyAI

Georgios Spithourakis

Former PhD Student

Publications

Language models as Knowledgebases?

In EMNLP 2019.
Evaluating Rewards for Question Generation Models

In ACL 2019.
Evaluating Rewards for Question Generation Models

In NAACL, 2019.
Interpretation of Natural Language Rules in Conversational Machine Reading

In EMNLP, 2018.
Constructing Datasets for Multi-hop Reading Comprehension Across Documents

In ACL 2018.

View All →

Software

  • Cape is an open source large-scale open-domain Question Answering system.

  • stat-nlp-book is an interactive Statistical NLP book in Python, used for our StatNLP from 2016 onwards.

  • stat-nlp-book-scala is an interactive Statistical NLP book in Scala, used for our StatNLP course in 2015 / 16.

  • Jack the Reader is a Machine Reading framework for Question Answering, Natural Language Inference, and Link Prediction - see the paper here.

  • Neural Theorem Prover is an end-to-end differentiable logic reasoner, implementing the model described in End-to-end Differentiable Proving.

  • Inferbeddings is a link prediction framework that allows including First-Order background knowledge via adversarial training - the model is described in Adversarial Sets for Regularising Neural Link Predictors.

  • wolfe is a framework for building rich machine learning models, based on functional programming, factor graphs, optimization and composition.

  • ucleed is a biomedical event extractor that ranked first in several tracks of the BioNLP 2011 shared task.

  • thebeast is a Markov Logic inference and learning engine.

  • What's Wrong With My NLP? is a visualizer for NLP problems.

Datasets

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.