Search Results for author:
Found 3 papers, 0 papers with code
Word Boundary Information Isn't Useful for Encoder Language Models
As such, removing these symbols has been shown to have a beneficial effect on the processing of morphologically complex words for transformer encoders in the pretrain-finetune paradigm.
Sample Efficient Approaches for Idiomaticity Detection
In particular we study the impact of Pattern Exploit Training (PET), a few-shot method of classification, and BERTRAM, an efficient method of creating contextual embeddings, on the task of idiomaticity detection.
drsphelps at SemEval-2022 Task 2: Learning idiom representations using BERTRAM
This paper describes our system for SemEval-2022 Task 2 Multilingual Idiomaticity Detection and Sentence Embedding sub-task B.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
