In-Context Learning and Fine-Tuning GPT for Argument Mining

Understand

Large Language Models (LLMs) have become ubiquitous in NLP and deep learning.

• In-Context Learning (ICL) has been suggested as a bridging paradigm between the training-free and fine-tuning LLMs settings.
• In ICL, an LLM is conditioned to solve tasks by means of a few solved demonstration examples included as prompt.
• Argument Mining (AM) aims to extract the complex argumentative structure of a text, and Argument Type Classification (ATC) is an essential sub-task of AM.