AutoSpec: An Agentic Framework for Automatically Drafting Patent Specification

Ryan Shea, Zhou Yu


Abstract
Patents play a critical role in driving technological innovation by granting inventors exclusive rights to their inventions. However the process of drafting a patent application is often expensive and time-consuming, making it a prime candidate for automation. Despite recent advancements in language models, several challenges hinder the development of robust automated patent drafting systems. First, the information within a patent application is highly confidential, which often prevents the use of closed-source LLMs for automating this task. Second, the process of drafting a patent application is difficult for even the most advanced language models due to their long context, technical writing style, and specialized domain knowledge. To address these challenges, we introduce AutoSpec, a secure, agentic framework for Automatically drafting patent Specification. Our approach decomposes the drafting process into a sequence of manageable subtasks, each solvable by smaller, open-source language models enhanced with custom tools tailored for drafting patent specification. To assess our system, we design a novel evaluation protocol in collaboration with experienced patent attorneys. Our automatic and expert evaluations show that AutoSpec outperforms existing baselines on a patent drafting task.
Anthology ID:
2025.findings-emnlp.687
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2025
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Christos Christodoulopoulos, Tanmoy Chakraborty, Carolyn Rose, Violet Peng
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
12829–12840
Language:
URL:
https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.687/
DOI:
10.18653/v1/2025.findings-emnlp.687
Bibkey:
Cite (ACL):
Ryan Shea and Zhou Yu. 2025. AutoSpec: An Agentic Framework for Automatically Drafting Patent Specification. In Findings of the Association for Computational Linguistics: EMNLP 2025, pages 12829–12840, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
AutoSpec: An Agentic Framework for Automatically Drafting Patent Specification (Shea & Yu, Findings 2025)
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PDF:
https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.687.pdf
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