In this paper, we evaluate the effect of a Transformer-based model with cross-lingual zero-shot learning to improve the reverse dictionary performance.

In this paper, we evaluate the effect of a Transformer-based model with cross-lingual zero-shot learning to improve the reverse dictionary performance. Our ...

In this paper , we evaluate the Transformer-based model with the added LSTM layer for the task at hand in a monolingual, multilingual, and cross-lingual zero- ...

JSI at SemEval-2022 Task 1: CODWOE - Reverse Dictionary: Monolingual and cross-lingual approaches. Editors. Emerson, G. Schluter, N. Stanovsky, G. Kumar, R.

JSI at SemEval-2022 Task 1: CODWOE - Reverse Dictionary: Monolingual and cross-lingual approaches. T. Hanh, M. Martinc, M. Purver, and S. Pollak.

We evaluate the Transformer-based model with the added LSTM layer for the task at hand in a monolingual, multilingual, and cross-lingual zero-shot setting in ...

2022/07/14 · JSI at SemEval-2022 Task 1: CODWOE - Reverse Dictionary: Monolingual, multilingual, and cross-lingual approaches. bookmark

This work proposes to focus on relating these opaque word vectors with human-readable definitions, as found in dictionaries, using comparable sets of ...

We evaluate the Transformer-based model with the added LSTM layer for the task at hand in a monolingual, multilingual, and cross-lingual zero-shot setting.

JSI at SemEval-2022 task 1 [Elektronski vir] : CODWOE - reverse dictionary : monolingual, multilingual, and cross-lingual approache. Hong Hanh, Tran Thi .