no code implementations • 4 Jul 2021 • Jeff Mitchell, Jeffrey S. Bowers
That shared features between train and test data are required for generalisation in artificial neural networks has been a common assumption of both proponents and critics of these models.
no code implementations • COLING 2020 • Jeff Mitchell, Jeffrey Bowers
Recently, domain-general recurrent neural networks, without explicit linguistic inductive biases, have been shown to successfully reproduce a range of human language behaviours, such as accurately predicting number agreement between nouns and verbs.
no code implementations • 25 Sep 2019 • Jeff Mitchell, Jeff Bowers
We argue that symmetry is an important consideration in addressing the problem of systematicity and investigate two forms of symmetry relevant to symbolic processes.
no code implementations • WS 2018 • Takuma Yoneda, Jeff Mitchell, Johannes Welbl, Pontus Stenetorp, Sebastian Riedel
In this paper we describe our 2nd place FEVER shared-task system that achieved a FEVER score of 62. 52{\%} on the provisional test set (without additional human evaluation), and 65. 41{\%} on the development set.
1 code implementation • ACL 2018 • Dirk Weissenborn, Pasquale Minervini, Isabelle Augenstein, Johannes Welbl, Tim Rockt{\"a}schel, Matko Bo{\v{s}}njak, Jeff Mitchell, Thomas Demeester, Tim Dettmers, Pontus Stenetorp, Sebastian Riedel
For example, in Question Answering, the supporting text can be newswire or Wikipedia articles; in Natural Language Inference, premises can be seen as the supporting text and hypotheses as questions.
2 code implementations • 20 Jun 2018 • Dirk Weissenborn, Pasquale Minervini, Tim Dettmers, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bošnjak, Jeff Mitchell, Thomas Demeester, Pontus Stenetorp, Sebastian Riedel
For example, in Question Answering, the supporting text can be newswire or Wikipedia articles; in Natural Language Inference, premises can be seen as the supporting text and hypotheses as questions.
no code implementations • WS 2018 • Jeff Mitchell, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel
We argue that extrapolation to examples outside the training space will often be easier for models that capture global structures, rather than just maximise their local fit to the training data.
no code implementations • NAACL 2018 • Vicente Ivan Sanchez Carmona, Jeff Mitchell, Sebastian Riedel
Natural Language Inference is a challenging task that has received substantial attention, and state-of-the-art models now achieve impressive test set performance in the form of accuracy scores.
no code implementations • 22 Apr 2018 • Jeff Mitchell, Sebastian Riedel
We investigate applying repurposed generic QA data and models to a recently proposed relation extraction task.
no code implementations • EACL 2017 • Renars Liepins, Ulrich Germann, Guntis Barzdins, Alex Birch, ra, Steve Renals, Susanne Weber, Peggy van der Kreeft, Herv{\'e} Bourlard, Jo{\~a}o Prieto, Ond{\v{r}}ej Klejch, Peter Bell, Alex Lazaridis, ros, Alfonso Mendes, Sebastian Riedel, Mariana S. C. Almeida, Pedro Balage, Shay B. Cohen, Tomasz Dwojak, Philip N. Garner, Andreas Giefer, Marcin Junczys-Dowmunt, Hina Imran, David Nogueira, Ahmed Ali, Mir, Sebasti{\~a}o a, Andrei Popescu-Belis, Lesly Miculicich Werlen, Nikos Papasarantopoulos, Abiola Obamuyide, Clive Jones, Fahim Dalvi, Andreas Vlachos, Yang Wang, Sibo Tong, Rico Sennrich, Nikolaos Pappas, Shashi Narayan, Marco Damonte, Nadir Durrani, Sameer Khurana, Ahmed Abdelali, Hassan Sajjad, Stephan Vogel, David Sheppey, Chris Hernon, Jeff Mitchell
We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5