arxiv Preprint – Link-Context Learning for Multimodal LLMs

In this episode we discuss Link-Context Learning for Multimodal LLMs
by Yan Tai, Weichen Fan, Zhao Zhang, Feng Zhu, Rui Zhao, Ziwei Liu. The paper presents a method called link-context learning (LCL) that enhances the learning abilities of Multimodal Large Language Models (MLLMs). LCL aims to enable MLLMs to recognize new images and understand unfamiliar concepts without the need for training. It focuses on strengthening the causal relationship between the support set and the query set to help MLLMs discern analogies and causal associations between data points. Experimental results demonstrate that the proposed LCL-MLLM performs better in link-context learning compared to traditional MLLMs.