题目：Applications of Model Evolution in Few-Shot Graph Learning and Exploration of Large language Model Self-Evolution Mechanisms.
报告人：李东（哈尔滨工业大学）
时间：2024.10.14 ，9：00-10：00
地点：明德楼B201-1
摘要：This report explores the application of model evolution in few-shot learning on graphs and graph representation learning, with a particular focus on enhancing the generalization ability of models in few-shot scenarios through continuous learning mechanisms. Building on this foundation, we further investigate the self-evolution mechanisms of large language models, including experience acquisition, self-optimization in dynamic environments, and potential self-feedback mechanisms. Finally, we provide insights into the prospects of leveraging graph neural networks to facilitate the self-evolution of large language models.
更多信息：研究生研讨班
