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Found 3 papers, 1 papers with code
MarSan at SemEval-2022 Task 11: Multilingual complex named entity recognition using T5 and transformer encoder
The multilingual complex named entity recognition task of SemEval2020 required participants to detect semantically ambiguous and complex entities in 11 languages.
MarSan at SemEval-2022 Task 6: iSarcasm Detection via T5 and Sequence Learners
Inspired by this, we propose a novel deep learning model on top of language models.
BERT-DRE: BERT with Deep Recursive Encoder for Natural Language Sentence Matching
Three Bi-LSTM layers with residual connection are used to design a recursive encoder and an attention module is used on top of this encoder.
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