Abstract
Semeval 2023 task 1: VWSD, In this paper, we propose an ensemble of two Neural network systems that ranks 10 images given a word and limited textual context. We have used openAI Clip based models for the English language and multilingual text-to-text translation models for Farsi-to-English and Italian-to-English. Additionally, we propose a system that learns from multilingual bert-base embeddings for text and resnet101 embeddings for the image. Considering all the three languages into account this system has achieved the fourth rank.- Anthology ID:
- 2023.semeval-1.176
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1271–1275
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.176
- DOI:
- 10.18653/v1/2023.semeval-1.176
- Cite (ACL):
- Rahul Patil, Pinal Patel, Charin Patel, and Mangal Verma. 2023. Rahul Patil at SemEval-2023 Task 1: V-WSD: Visual Word Sense Disambiguation. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1271–1275, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Rahul Patil at SemEval-2023 Task 1: V-WSD: Visual Word Sense Disambiguation (Patil et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2023.semeval-1.176.pdf