activity
20212024
most citedMulti-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation

2 citations · 7 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2024★ 1 cited

Teaching Smaller Language Models To Generalise To Unseen Compositional Questions (Full Thesis)

Tim Hartill

Pretrained large Language Models (LLMs) are able to answer questions that are unlikely to have been encountered during training. However a diversity of potential applications exist…

cs.CL2023

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…

cs.CL2023

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…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 2 cited

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…

cs.CL2022★ 2 cited

Multi-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation

Qiming Bao, Alex Yuxuan Peng, Tim Hartill +4

Combining deep learning with symbolic logic reasoning aims to capitalize on the success of both fields and is drawing increasing attention. Inspired by DeepLogic, an end-to-end mod…

q-bio.NC2021★ 1 cited

Relating Blindsight and AI: A Review

Joshua Bensemann, Qiming Bao, Gaël Gendron +2

Processes occurring in brains, a.k.a. biological neural networks, can and have been modeled within artificial neural network architectures. Due to this, we have conducted a review…