/ Ideas / Accurate LLM/RAG summarisation for conservation evidence literature

This is an idea proposed in 2024 as a Cambridge Computer Science Part II project, and is available for being worked on. It will be supervised by Anil Madhavapeddy and Sadiq Jaffer as part of my Conservation Evidence Copilots project.

Summary

At the Conservation Evidence Copilots project, we are interested in finding and synthesising evidence for conservation interventions. Once the text has been retrieved, it needs to be summarised in a way that is accurate, concise and relevant. This is particularly important for conservation evidence, where the key findings need to be communicated clearly to inform policy and practice.

This project investigates how to verify the accuracy of summaries generated by LLMs and RAG pipelines for CE literature. Our goal is to develop a pipeline that can reliably go from extracting relevant information from text to a summary that is verifiably (by a human) correct.

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