Back to search

Article

Remember, Retrieve and Generate: Understanding Infinite Visual Concepts as Your Personalized Assistant

2024-11-28

Abstract excerpt

The development of large language models (LLMs) has significantly enhanced the capabilities of multimodal LLMs (MLLMs) as general assistants. However, lack of user-specific knowledge still restricts their application in human’s daily life. In this paper, we introduce the Retrieval Augmented Personalization (RAP) framework for MLLMs’ personalization. Starting from a general MLLM, we turn it into a personalized assi...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
7b60dc21-728d-52e8-a1e9-b6766f02240f
DOI
10.32388/95w7kc
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Remember, Retrieve and Generate: Understanding Infinite Visual Concepts as Your Personalized AssistantDOI 10.32388/95w7kc
Select a neighboring publication to make it the new centre.