PetKaz at SemEval-2024 Task 3: Advancing Emotion Classification with an LLM for Emotion-Cause Pair Extraction in Conversations

• URL: http://arxiv.org/abs/2404.05502v1
• Date: Mon, 8 Apr 2024 13:25:03 GMT
• Title: PetKaz at SemEval-2024 Task 3: Advancing Emotion Classification with an LLM for Emotion-Cause Pair Extraction in Conversations
• Authors: Roman Kazakov, Kseniia Petukhova, Ekaterina Kochmar,
• Abstract summary: We present our submission to the SemEval-2023 Task3 "The Competition of Multimodal Emotion Cause Analysis in Conversations" Our approach relies on combining fine-tuned GPT-3.5 for emotion classification and a BiLSTM-based neural network to detect causes.
• Score: 4.463184061618504
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we present our submission to the SemEval-2023 Task~3 "The Competition of Multimodal Emotion Cause Analysis in Conversations", focusing on extracting emotion-cause pairs from dialogs. Specifically, our approach relies on combining fine-tuned GPT-3.5 for emotion classification and a BiLSTM-based neural network to detect causes. We score 2nd in the ranking for Subtask 1, demonstrating the effectiveness of our approach through one of the highest weighted-average proportional F1 scores recorded at 0.264.

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