KAUCUS: Knowledge Augmented User Simulators for Training Language Model Assistants. (arXiv:2401.16454v1 [cs.HC])

An effective multi-turn instruction-following assistant can be developed by
creating a simulator that can generate useful interaction data. Apart from
relying on its intrinsic weights, an ideal user simulator should also be able
to bootstrap external knowledge rapidly in its raw form to simulate the
multifarious diversity of text available over the internet. Previous user
simulators generally lacked diversity, were mostly closed domain, and
necessitated rigid schema making them inefficient to rapidly scale to
incorporate external knowledge. In this regard, …

arxiv assistant assistants bootstrap cs.hc data diversity form generate intrinsic knowledge language language model raw training