Summary of Towards Automated Patent Workflows: Ai-orchestrated Multi-agent Framework For Intellectual Property Management and Analysis, by Sakhinana Sagar Srinivas et al.
Towards Automated Patent Workflows: AI-Orchestrated Multi-Agent Framework for Intellectual Property Management and Analysis
by Sakhinana Sagar Srinivas, Vijay Sri Vaikunth, Venkataramana Runkana
First submitted to arxiv on: 21 Sep 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper presents PatExpert, an autonomous multi-agent conversational framework designed to streamline and optimize patent-related tasks. The framework consists of a metaagent that coordinates task-specific expert agents for various patent-related tasks, including patent classification, acceptance, claim generation, abstractive summarization, multi-patent analysis, and scientific hypothesis generation. The framework incorporates advanced methods like Graph Retrieval-Augmented Generation (GRAG) to enhance response accuracy and relevance by combining semantic similarity with knowledge graphs. The paper also discusses the importance of explainability in patent analysis, ensuring transparent justifications for decisions made during patent processing. Empirical evidence demonstrates significant improvements in patent processing tasks, concluding that the framework offers a robust solution for automating and optimizing patent analysis. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper creates an AI tool called PatExpert to help with patent work. It’s like a super-smart assistant that can do lots of things, like understanding patents, making summaries, and even helping with big scientific ideas. The tool is special because it can explain why it made certain decisions, which is important for keeping track of who owns what ideas. By using this tool, people doing patent work might be able to get their jobs done faster and more accurately. |
Keywords
» Artificial intelligence » Classification » Retrieval augmented generation » Summarization
