183 citations · 455 across the 31 of their papers we have counts for
39 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…
Atomic Inference for NLI with Generated Facts as Atoms
Joe Stacey, Pasquale Minervini, Haim Dubossarsky +2
With recent advances, neural models can achieve human-level performance on various natural language tasks. However, there are no guarantees that any explanations from these models…
Distilling Robustness into Natural Language Inference Models with Domain-Targeted Augmentation
Joe Stacey, Marek Rei
Knowledge distillation optimises a smaller student model to behave similarly to a larger teacher model, retaining some of the performance benefits. While this method can improve re…
Finding the Needle in a Haystack: Unsupervised Rationale Extraction from Long Text Classifiers
Kamil Bujel, Andrew Caines, Helen Yannakoudakis +1
Long-sequence transformers are designed to improve the representation of longer texts by language models and their performance on downstream document-level tasks. However, not much…
Modelling Temporal Document Sequences for Clinical ICD Coding
Clarence Boon Liang Ng, Diogo Santos, Marek Rei
Past studies on the ICD coding problem focus on predicting clinical codes primarily based on the discharge summary. This covers only a small fraction of the notes generated during…
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…