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

8 Apr 2024arXiv:2404.05502archive 2025-07-28

Roman Kazakov, Kseniia Petukhova, Ekaterina Kochmar

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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sachertort/petkaz-semeval-ecac officialmentioned in papermentioned on GitHubpytorch report

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Emotion ClassificationEmotion-Cause Pair Extraction

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Methods

AdamAttentionAttention DropoutBPECosine AnnealingDense ConnectionsDropoutGPT-3Layer NormalizationLinear LayerLinear Warmup With Cosine AnnealingMulti-Head AttentionResidual ConnectionSoftmaxWeight Decay

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