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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16337
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dc.contributor.authorSharma, Yashvardhan-
dc.date.accessioned2024-11-12T07:08:01Z-
dc.date.available2024-11-12T07:08:01Z-
dc.date.issued2024-
dc.identifier.urihttps://aclanthology.org/2024.semeval-1.115/-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16337-
dc.description.abstractEmotion Recognition in Conversation (ERC)aims to assign an emotion to a dialogue in aconversation between people. The first subtaskof EDiReF shared task aims to assign an emo-tions to a Hindi-English code mixed conversa-tion. For this, our team proposes a system toidentify the emotion based on fine-tuning largelanguage models on the MaSaC dataset. Forour study we have fine tuned 2 LLMs BERTand Llama 2 to perform sequence classification to identify the emotion of the text.en_US
dc.language.isoenen_US
dc.publisherAssociation for Computational Linguisticsen_US
dc.subjectComputer Scienceen_US
dc.subjectEmotion Recognition in Conversation (ERC)en_US
dc.subjectHindi-English codeen_US
dc.titleBITS Pilani at SemEval-2024 Task 10: Fine-tuning BERT and Llama 2 for Emotion Recognition in Conversationen_US
dc.typeArticleen_US
Appears in Collections:Department of Computer Science and Information Systems

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