Fine-Tuning Large Language Models for Standards and Claim Chart Mapping

XLSCOUT Ltd. specializes in AI-driven patent intelligence, providing advanced solutions for intellectual property (IP) strategy and innovation management. The company aims to enhance the accuracy and efficiency of patent-related tasks, such as claim chart generation and standards compliance mapping, through fine-tuned large language models (LLMs).
This project addresses a critical challenge: general-purpose LLMs lack domain-specific understanding required for precise claim chart mapping and regulatory compliance. By fine-tuning LLMs for standards interpretation and automated claim chart generation, the project will significantly reduce manual effort while improving accuracy and consistency in patent validation.
The anticipated benefits for XLSCOUT include enhanced AI-driven tools that improve workflow efficiency for IP professionals, reducing time and cost associated with claim chart creation. This will strengthen XLSCOUT’s competitive position in the patent intelligence market by offering a unique AI-powered solution tailored to industry needs.
Beyond XLSCOUT, the broader IP sector will benefit from more reliable and standardized claim chart mapping, leading to improved patent litigation and enforcement. Additionally, this research will contribute to advancements in AI applications for legal and technical documentation, demonstrating the potential for LLMs in specialized regulatory domains.

Faculty Supervisor:

Gerald Penn;Frank Rudzicz

Student:

Partner:

XLSCOUT

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program: