Abstract
This paper describes our contribution to SemEval 2023 Task 8: Brainteaser. We compared multiple zero-shot approaches using GPT-4, the state of the art model with Mistral-7B, a much smaller open-source LLM. While GPT-4 remains a clear winner in all the zero-shot approaches, we show that finetuning Mistral-7B can achieve comparable, even though marginally lower results.- Anthology ID:
- 2024.semeval-1.200
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1391–1396
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.200
- DOI:
- 10.18653/v1/2024.semeval-1.200
- Cite (ACL):
- Kejsi Take and Chau Tran. 2024. RiddleMasters at SemEval-2024 Task 9: Comparing Instruction Fine-tuning with Zero-Shot Approaches. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 1391–1396, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- RiddleMasters at SemEval-2024 Task 9: Comparing Instruction Fine-tuning with Zero-Shot Approaches (Take & Tran, SemEval 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.200.pdf