Ukrainian Visual Word Sense Disambiguation Benchmark

1. 1Construct a dataset with ambiguous words and corresponding images
2. 2Annotate the dataset with correct sense labels
3. 3Evaluate the performance of Visual-WSD models on the benchmark
4. 4Fine-tune and compare the results of different models on the Ukrainian Visual-WSD task

NLP researchers and AI engineers working on multilingual models can benefit from this benchmark to evaluate and improve their models' performance on Ukrainian language tasks. The benchmark can also be useful for data scientists and machine learning researchers interested in word sense disambiguation and visual understanding

💡 The benchmark provides a methodology for evaluating Visual-WSD models in Ukrainian, which can help improve the performance of NLP models on this language

🇺🇦 Introducing Ukrainian Visual Word Sense Disambiguation Benchmark for evaluating #VisualWSD models