3 accepted papers
This paper tackles the fundamental failure of Large Language Models (LLMs) to solve new tasks when prompted with a sufficient, yet overly complex, set of multi-modal episodes. This failure stems from the model
Human image synthesis with pose guidance generates images of a specified human in a given pose, a task complicated by dis-occlusions and varying body articulations. While generative model-based approaches are effective, they often require paired training data, limiting generalizability. Recent selfs…
Retrieval-Augmented Generation (RAG) has emerged as a promising technique to enhance the quality and relevance of responses generated by large language models. While recent advancements have mainly focused on improving RAG for text-based queries, RAG on multi-modal documents containing both texts an