Papers with adaptive logic graph network

1 papers
AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension (2022.acl-long)

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Challenge: Existing methods and limitations for machine reading comprehension are insufficient for logical reasoning over text.
Approach: They propose a neural-symbolic approach which passes messages over a graph representing logical relations between text units to predict an answer.
Outcome: The proposed approach outperforms existing methods on ReClor and LogiQA.

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