Papers with temporal attention

1 papers
Temporal Attention for Language Models (2022.findings-naacl)

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Challenge: Pretrained language models are trained on corpora derived from the web, but ignore this information.
Approach: They propose a time-aware self-attention mechanism that captures time-specific contextualized word representations and allows the transformer to capture this information.
Outcome: The proposed model achieves state-of-the-art on three datasets in different languages (English, German, and Latin) that vary in time, size, and genre.

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