Papers with single-sentence prediction tasks

1 papers
Frustratingly Easy Performance Improvements for Low-resource Setups: A Tale on BERT and Segment Embeddings (2022.lrec-1)

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Challenge: Understanding why contextualized embeddings work is still an active area of research.
Approach: They propose to use a BERT architecture to encode a sub-word, position and a segment embedding as input representations for each sub- word.
Outcome: The proposed model performs well on single-sentence prediction tasks while swapping segment IDs in paired-sentent tasks.

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