Papers with TSLM

1 papers
Time-Stamped Language Model: Teaching Language Models to Understand The Flow of Events (2021.naacl-main)

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Challenge: Using transformer-based language models to track entities is challenging due to dynamic nature of the world described in the text.
Approach: They propose to use transformer-based language models to track entities throughout a procedure . they propose to introduce timestamp encoding to encode event information in LMs .
Outcome: The proposed model improves on the state-of-the-art model with a 3.1% increase in F1 score on the Propara dataset and better results on the location prediction task on the NPN-Cooking dataset.

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