title: Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized
    Academic Assistance
summary: 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.
paper_authors._id: 66e00fc1fba5a55441e57188
paper_authors.name: Guanyu Lin
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-10T09:45:35.616Z
paper_authors._id: 6586a7a84f9d2b955ee21b0d
paper_authors.avatarUrl: /avatars/4f55c26fe62a12aab8f1413387d2e75a.svg
paper_authors.fullname: Guanyu Lin
paper_authors.type: user
paper_authors.user: cmulgy
paper_authors._id: 66e00fc1fba5a55441e57189
paper_authors.name: Tao Feng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-10T09:48:20.681Z
paper_authors._id: 66269e8b3385ba4e6ed75834
paper_authors.avatarUrl: /avatars/a3188fbb4526f62db92dc65ce42598bc.svg
paper_authors.fullname: Tao Feng
paper_authors.type: user
paper_authors.user: taofeng
paper_authors._id: 66e00fc1fba5a55441e5718a
paper_authors.name: Pengrui Han
paper_authors._id: 66e00fc1fba5a55441e5718b
paper_authors.name: Ge Liu
paper_authors._id: 66e00fc1fba5a55441e5718c
paper_authors.name: Jiaxuan You
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-09-10T09:46:44.321Z
paper_authors._id: 64db38efa21d6c044ba64f78
paper_authors.avatarUrl: /avatars/e55eae7bf27af4c9c829723ac939eb56.svg
paper_authors.fullname: Jiaxuan
paper_authors.type: user
paper_authors.user: youjiaxuan
paper_title: Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized
    Academic Assistance
paper_summary: 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.
paper_ai_summary: Paper Copilot is a self-evolving LLM system that provides personalized academic support and streamlines the research process by maintaining a real-time updated database and saving researchers time.
paper_ai_keywords: LLM thought-retrieval user profile high performance optimization personalized research services