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cs.CL2022★ 24 cited
Large Language Models Can Self-Improve
Jiaxin Huang, Shixiang Shane Gu, Le Hou +4
Large Language Models (LLMs) have achieved excellent performances in various tasks. However, fine-tuning an LLM requires extensive supervision. Human, on the other hand, may improv…
cs.CL2022
Continual Sequence Generation with Adaptive Compositional Modules
Yanzhe Zhang, Xuezhi Wang, Diyi Yang
Continual learning is essential for real-world deployment when there is a need to quickly adapt the model to new tasks without forgetting knowledge of old tasks. Existing work on c…