115 citations · 119 across the 4 of their papers we have counts for
6 papers
On the application of Large Language Models for language teaching and assessment technology
Andrew Caines, Luca Benedetto, Shiva Taslimipoor +12
The recent release of very large language models such as PaLM and GPT-4 has made an unprecedented impact in the popular media and public consciousness, giving rise to a mixture of…
An Extended Sequence Tagging Vocabulary for Grammatical Error Correction
Stuart Mesham, Christopher Bryant, Marek Rei +1
We extend a current sequence-tagging approach to Grammatical Error Correction (GEC) by introducing specialised tags for spelling correction and morphological inflection using the S…
Grammatical Error Correction: A Survey of the State of the Art
Christopher Bryant, Zheng Yuan, Muhammad Reza Qorib +3
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as mi…
Probing for targeted syntactic knowledge through grammatical error detection
Christopher Davis, Christopher Bryant, Andrew Caines +2
Targeted studies testing knowledge of subject-verb agreement (SVA) indicate that pre-trained language models encode syntactic information. We assert that if models robustly encode…
Contextual Sentence Classification: Detecting Sustainability Initiatives in Company Reports
Dan Hirlea, Christopher Bryant, Maurizio Zollo +1
We introduce the novel task of detecting sustainability initiatives in company reports. Given a full report, the aim is to automatically identify mentions of practical activities t…
Neural Grammatical Error Correction with Finite State Transducers
Felix Stahlberg, Christopher Bryant, Bill Byrne
Grammatical error correction (GEC) is one of the areas in natural language processing in which purely neural models have not yet superseded more traditional symbolic models. Hybrid…