2 citations · 7 across the 7 of their papers we have counts for
4 papers · 2 filters
Do Smaller Language Models Answer Contextualised Questions Through Memorisation Or Generalisation?
Tim Hartill, Joshua Bensemann, Michael Witbrock +1
A distinction is often drawn between a model's ability to predict a label for an evaluation sample that is directly memorised from highly similar training samples versus an ability…
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…
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…