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