121 citations · 271 across the 25 of their papers we have counts for
25 papers
Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language Models
Qiming Bao, Juho Leinonen, Alex Yuxuan Peng +7
Large language models exhibit superior capabilities in processing and understanding language, yet their applications in educational contexts remain underexplored. Learnersourcing e…
Teaching Smaller Language Models To Generalise To Unseen Compositional Questions
Tim Hartill, Neset Tan, Michael Witbrock +1
We equip a smaller Language Model to generalise to answering challenging compositional questions that have not been seen in training. To do so we propose a combination of multitask…
Answering Unseen Questions With Smaller Language Models Using Rationale Generation and Dense Retrieval
Tim Hartill, Diana Benavides-Prado, Michael Witbrock +1
When provided with sufficient explanatory context, smaller Language Models have been shown to exhibit strong reasoning ability on challenging short-answer question-answering tasks…
Large Language Models Are Not Strong Abstract Reasoners
Gaël Gendron, Qiming Bao, Michael Witbrock +1
Large Language Models have shown tremendous performance on a large variety of natural language processing tasks, ranging from text comprehension to common sense reasoning. However,…
Input-length-shortening and text generation via attention values
Neşet Özkan Tan, Alex Yuxuan Peng, Joshua Bensemann +4
Identifying words that impact a task's performance more than others is a challenge in natural language processing. Transformers models have recently addressed this issue by incorpo…
Disentanglement of Latent Representations via Causal Interventions
Gaël Gendron, Michael Witbrock, Gillian Dobbie
The process of generating data such as images is controlled by independent and unknown factors of variation. The retrieval of these variables has been studied extensively in the di…