Licheng Zhang

DACL-RAG: Data Augmentation Strategy with Curriculum Learning for Retrieval-Augmented Generation

2025 · arXiv (Cornell University)

Retrieval-Augmented Generation (RAG) is an effective method to enhance the capabilities of large language models (LLMs). Existing methods typically optimize the retriever or the generator in a RAG system by directly using the top-k retrieved …

Curriculum Learning for Natural Language Understanding

2020

With the great success of pre-trained language models, the pretrain-finetune paradigm now becomes the undoubtedly dominant solution for natural language understanding (NLU) tasks. At the fine-tune stage, target task data is usually introduced in a …