Imagination Augmented Generation: Learning to Imagine Richer Context for Question Answering over Large Language Models

1 code implementation • 22 Mar 2024 • Huanxuan Liao, Shizhu He, Yao Xu, Yuanzhe Zhang, Kang Liu, Shengping Liu, Jun Zhao

Retrieval-Augmented-Generation and Gener-ation-Augmented-Generation have been proposed to enhance the knowledge required for question answering over Large Language Models (LLMs).

Open-Domain Question Answering

LMTuner: An user-friendly and highly-integrable Training Framework for fine-tuning Large Language Models

1 code implementation • 20 Aug 2023 • Yixuan Weng, Zhiqi Wang, Huanxuan Liao, Shizhu He, Shengping Liu, Kang Liu, Jun Zhao

With the burgeoning development in the realm of large language models (LLMs), the demand for efficient incremental training tailored to specific industries and domains continues to increase.