| dc.contributor.author |
Sharma, Yashvardhan |
|
| dc.date.accessioned |
2024-11-12T07:08:01Z |
|
| dc.date.available |
2024-11-12T07:08:01Z |
|
| dc.date.issued |
2024 |
|
| dc.identifier.uri |
https://aclanthology.org/2024.semeval-1.115/ |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16337 |
|
| dc.description.abstract |
Emotion 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.iso |
en |
en_US |
| dc.publisher |
Association for Computational Linguistics |
en_US |
| dc.subject |
Computer Science |
en_US |
| dc.subject |
Emotion Recognition in Conversation (ERC) |
en_US |
| dc.subject |
Hindi-English code |
en_US |
| dc.title |
BITS Pilani at SemEval-2024 Task 10: Fine-tuning BERT and Llama 2 for Emotion Recognition in Conversation |
en_US |
| dc.type |
Article |
en_US |