Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized
  Academic Assistance
Authors: name: Guanyu Lin, name: Tao Feng, name: Pengrui Han, name: Ge Liu, name: Jiaxuan You

As scientific research proliferates, researchers face the daunting task of
navigating and reading vast amounts of literature. Existing solutions, such as
document QA, fail to provide personalized and up-to-date information
efficiently. We present Paper Copilot, a self-evolving, efficient LLM system
designed to assist researchers, based on thought-retrieval, user profile and
high performance optimization. Specifically, Paper Copilot can offer
personalized research services, maintaining a real-time updated database.
Quantitative evaluation demonstrates that Paper Copilot saves 69.92\% of time
after efficient deployment. This paper details the design and implementation of
Paper Copilot, highlighting its contributions to personalized academic support
and its potential to streamline the research process.