Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues

arXiv:2404.11095v1 Announce Type: new
Abstract: Aligning large language models (LLMs) with human expectations requires high-quality instructional dialogues, which can be achieved by raising diverse, in-depth, and insightful instructions that deepen interactions. Existing methods target instructions from real instruction dialogues as a learning goal and fine-tune a user simulator for posing instructions. However, the user simulator struggles to implicitly model complex dialogue flows and pose high-quality instructions. In this paper, we take inspiration from the cognitive abilities inherent in human learning …

abstract arxiv cs.ai cs.cl diverse however human inductive interactions language language models large language large language models llms quality simulator strategy type