Papers by Chandrai Kayal
JLBert: Japanese Light BERT for Cross-Domain Short Text Classification (2024.lrec-main)
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| Challenge: | Short Texts face the problem of being short, equivocal, and non-standard. |
| Approach: | They propose a Japanese BERT model with cross-domain functionality and comparable accuracy to State of the Art models. |
| Outcome: | The proposed model outperforms state-of-the-art models on three short text datasets by 1.5% across various domains. |