10 papers
Benchmarking Patent Drafting from Inventor-Style Disclosures
Lekang Jiang, Wenjun Sun, Stephan Goetz
While recent large language models (LLMs) have achieved promising results on individual patent drafting tasks, they fundamentally fail to investigate the core challenge of real-wor…
ADIAS: Automated Design of Interactive Agentic Systems
Lekang Jiang, Bohan Tang, Stephan Goetz +1
Automated agent design improves agent harnesses through iterative revision, evaluation, and feedback summarization. Existing methods are largely candidate-centric: cross-round expe…
When Reasoning Hurts Legal Drafting: The Verbalization Bottleneck in Patent Claim Generation
Lekang Jiang, Wenjun Sun, Stephan Goetz
Patent claim drafting is a challenging legal drafting task that requires technical expertise, precise linguistic control, strict adherence to formal conventions, and the preservati…
Reasoning for Hierarchical Text Classification: The Case of Patents
Lekang Jiang, Wenjun Sun, Stephan Goetz
Hierarchical text classification (HTC) assigns documents to multiple levels of a pre-defined taxonomy. Automated patent subject classification represents one of the hardest HTC sce…
Can Large Language Models Understand As Well As Apply Patent Regulations to Pass a Hands-On Patent Attorney Test?
Bhakti Khera, Rezvan Alamian, Pascal A. Scherz +1
The legal field already uses various large language models (LLMs) in actual applications, but their quantitative performance and reasons for it are underexplored. We evaluated seve…
Patent-CR: A Dataset for Patent Claim Revision
Lekang Jiang, Pascal A Scherz, Stephan Goetz
This paper presents Patent-CR, the first dataset created for the patent claim revision task in English. It includes both initial patent applications rejected by patent examiners an…