Abstract
In this study, we propose using the GPT-3 as a query generator for the backend of CLIP as an implicit word sense disambiguation (WSD) component for the SemEval 2023 shared task Visual Word Sense Disambiguation (VWSD). We confirmed previous findings — human-like prompts adapted for WSD with quotes benefit both CLIP and GPT-3, whereas plain phrases or poorly templated prompts give the worst results.- Anthology ID:
- 2023.starsem-1.36
- Volume:
- Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Alexis Palmer, Jose Camacho-collados
- Venue:
- *SEM
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 417–422
- Language:
- URL:
- https://aclanthology.org/2023.starsem-1.36
- DOI:
- 10.18653/v1/2023.starsem-1.36
- Cite (ACL):
- Xiaomeng Pan, Zhousi Chen, and Mamoru Komachi. 2023. Query Generation Using GPT-3 for CLIP-Based Word Sense Disambiguation for Image Retrieval. In Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), pages 417–422, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Query Generation Using GPT-3 for CLIP-Based Word Sense Disambiguation for Image Retrieval (Pan et al., *SEM 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2023.starsem-1.36.pdf