2 papers
cs.CL2025
Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data
Leonardo Castro-Gonzalez, Yi-Ling Chung, Hannak Rose Kirk +4
The field of machine learning has recently made significant progress in reducing the requirements for labelled training data when building new models. These `cheaper' learning tech…
cs.CL2024
MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks
John Francis, Saba Esnaashari, Anton Poletaev +3
Large language models (LLMs) have demonstrated remarkable capabilities in text analysis tasks, yet their evaluation on complex, real-world applications remains challenging. We defi…