GAVx at SemEval-2024 Task 10: Emotion Flip Reasoning via Stacked Instruction Finetuning of LLMs
Vy Nguyen, Xiuzhen Zhang · 2024
The Emotion Flip Reasoning task at SemEval 2024 aims at identifying the utterance(s) that trigger a speaker to shift from an emotion to another in a multi-party conversation.The spontaneous, informal, and occasionally multilingual dynamics of conversations make the task challenging.In this paper, we propose a supervised stacked instruction-based framework to finetune large language models to tackle this task.Utilising the annotated datasets provided, we curate multiple instruction sets involving chain-of-thoughts, feedback, and self-evaluation instructions, for a multi-step finetuning pipeline.We utilise the selfconsistency inference strategy to enhance prediction consistency.Experimental results reveal commendable performance, achieving mean F1 scores of 0.77 and 0.76 for triggers in the Hindi-English and English-only tracks respectively.This led to us earning the second highest ranking 1 in both tracks.