DGoT: Dynamic Graph of Thoughts for Scientific Abstract Generation

arXiv:2403.17491v1 Announce Type: new
Abstract: The method of training language models based on domain datasets has obtained significant achievements in the task of generating scientific paper abstracts. However, such models face problems of generalization and expensive training costs. The use of large language models (LLMs) to solve the task of generating paper abstracts saves the cost of model training. However, due to the hallucination problem of LLM, it is often necessary to improve the reliability of the results through multi-round …

abstract arxiv cs.cl dynamic graph scientific thoughts type