9 citations · 9 across the 1 of their papers we have counts for
3 papers · 1 filter
Increasing the Difficulty of Automatically Generated Questions via Reinforcement Learning with Synthetic Preference
William Thorne, Ambrose Robinson, Bohua Peng +2
As the cultural heritage sector increasingly adopts technologies like Retrieval-Augmented Generation (RAG) to provide more personalised search experiences and enable conversations…
Bio-SIEVE: Exploring Instruction Tuning Large Language Models for Systematic Review Automation
Ambrose Robinson, William Thorne, Ben P. Wu +4
Medical systematic reviews can be very costly and resource intensive. We explore how Large Language Models (LLMs) can support and be trained to perform literature screening when pr…
Navigating Prompt Complexity for Zero-Shot Classification: A Study of Large Language Models in Computational Social Science
Yida Mu, Ben P. Wu, William Thorne +5
Instruction-tuned Large Language Models (LLMs) have exhibited impressive language understanding and the capacity to generate responses that follow specific prompts. However, due to…