Papers with dynamic curriculum learning framework

2 papers
CLCL: Non-compositional Expression Detection with Contrastive Learning and Curriculum Learning (2023.acl-long)

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Challenge: Non-compositional expressions are a substantial challenge for natural language processing systems, necessitating more intricate processing compared to general language tasks.
Approach: They propose a dynamic curriculum learning framework specifically designed to take advantage of scarce available training data for modeling non-compositionality.
Outcome: The proposed framework improves on idiom usage recognition and metaphor detection tasks.
Non-compositional Expression Generation Based on Curriculum Learning and Continual Learning (2023.findings-emnlp)

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Challenge: Non-compositional expressions are a classic ‘pain in the neck’ for NLP systems because of their non-composibility and limited data resources.
Approach: They propose a dynamic curriculum learning framework which learns training examples from easy ones to harder ones but suffers from the forgetting problem.
Outcome: The proposed framework improves on idiomatic expression generation and metaphor generation.

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