Papers with continual learning method

3 papers
Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking (2021.acl-short)

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Challenge: Existing methods to learn consecutive tasks without forgetting how to perform previously trained problems are lacking.
Approach: They propose a continual learning method which preserves performance on previously encountered tasks while accelerating learning progress on subsequent tasks.
Outcome: The proposed method preserves performance on previously encountered tasks while accelerating learning progress on subsequent 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.
Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers (2021.emnlp-main)

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Challenge: Existing methods for continual learning for semantic parsing fail to account for special properties of structured outputs . retraining from scratch is not feasible due to the fast growing number of tasks .
Approach: They propose a continual learning method that uses sequential learning to learn tasks without accessing full training data from previous tasks.
Outcome: The proposed method achieves a 3-6 times speedup compared to re-training from scratch.

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