Papers by Kasidis Kanwatchara

1 papers
Rational LAMOL: A Rationale-based Lifelong Learning Framework (2021.acl-long)

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Challenge: Existing paradigms for machine learning suffer from catastrophic forgetting when a model completely forgets what it just learned in previous tasks.
Approach: They propose to exploit unsupervised rationale generation to improve the performance of a lifelong language learning model by applying critical freezing guided by human rationales.
Outcome: The proposed framework outperforms vanilla LAMOL on most permutations and unsupervised rationale generation consistently improves the overall performance.

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