Title:Applications of Model Evolution in Few-Shot Graph Learning and Exploration of Large language Model Self-Evolution Mechanisms.
Speaker:Dong Li (Harbin Institute of Technology)
Time:2024.10.14 ，9：00-10：00
Location: B201-1, Mingde Building
Abstract：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.
More information: Graduate Student Seminar
