Vibe Patenting: Evaluating LLM Judges for Professional Patent-Drafting Agents
Source
Toshiaki Koike-Akino, Vlad Blaykhman, Ye Wang, Jing Liu, Gene V. Vinokur
Author
Toshiaki Koike-Akino, Vlad Blaykhman, Ye Wang, Jing Liu, Gene V. Vinokur
Date
Terms in this piece · Glossary
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
Why it matters
Demonstrates that iterative LLMA large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.Full definition →-judge feedback can close much of the quality gap between cheap and expensive drafting agents on a complex professional task, and validates the judge's scores against a human expert, a useful pattern for building agentic document-drafting evalA repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.Full definition →.
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