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Computer Science > Computation and Language

arXiv:2409.04593 (cs)
[Submitted on 6 Sep 2024]

Title:Paper Copilot: A Self-Evolving and Efficient LLM System for Personalized Academic Assistance

Authors:Guanyu Lin, Tao Feng, Pengrui Han, Ge Liu, Jiaxuan You
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Abstract: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.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2409.04593 [cs.CL]
  (or arXiv:2409.04593v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2409.04593

Submission history

From: Guanyu Lin [view email]
[v1] Fri, 6 Sep 2024 20:04:04 UTC (1,896 KB)
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