April 9, 2024, 4:51 a.m. | Roman Kazakov, Kseniia Petukhova, Ekaterina Kochmar

cs.CL updates on arXiv.org arxiv.org

arXiv:2404.05502v1 Announce Type: new
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.

abstract analysis arxiv classification competition conversations cs.ai cs.cl emotion extraction gpt gpt-3 gpt-3.5 llm multimodal paper type

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