Papers by Shih-Ting Lin

2 papers
Conditional Generation of Temporally-ordered Event Sequences (2021.acl-long)

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Challenge: a new model of narrative schema knowledge does not capture the temporal relationships between events . a temporal order model is able to unscramble event sequences without access to labeled temporal training data .
Approach: They propose a temporal order-based model that can be flexibly applied to different tasks . they use a BART-based conditional generation model that captures temporal co-occurrence .
Outcome: The proposed model outperforms existing models on temporal ordering and event infilling tasks.
ReadOnce Transformers: Reusable Representations of Text for Transformers (2021.acl-long)

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Challenge: ReadOnce Transformers is a task-independent, task-dependent, and compressed representation of text.
Approach: They propose a transformer-based model that can build an information-capturing, task-independent, and compressed representation of text.
Outcome: The proposed model can build an information-capturing, task-independent, and compressed representation of text.

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