Name
Title | ||
|---|---|---|
HiJoNLP at SemEval-2022 Task 2: Detecting Idiomaticity of Multiword Expressions using Multilingual Pretrained Language Models. |
Abstract | ||
|---|---|---|
This paper describes an approach to detect idiomaticity only from the contextualized representation of a MWE over multilingual pretrained language models. Our experiments find that larger models are usually more effective in idiomaticity detection. However, using a higher layer of the model may not guarantee a better performance. In multilingual scenarios, the convergence of different languages are not consistent and rich-resource languages have big advantages over other languages. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.18653/v1/2022.semeval-1.23 | International Workshop on Semantic Evaluation (SemEval ) |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 1 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minghuan Tan | 1 | 0 | 2.03 |