Papers with multi-task text-to-text framework

1 papers
Promoting Graph Awareness in Linearized Graph-to-Text Generation (2021.findings-acl)

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Challenge: Recent applications of pretrained transformers to linearizations of graph inputs yield stateof-the-art results on graph-to-text tasks.
Approach: They propose to use pretrained transformers to encode local graph structures . they find they can improve the quality of models' implicit graph encodings .
Outcome: The proposed models can encode local graph structures and reconstruct corrupted inputs.

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