Comparing Complex Concepts with Transformers: Matching Patent Claims Against Natural Language Text
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Abstract (arXiv)
A key capability in managing patent applications or a patent portfolio is comparing claims to other text, e.g. a patent specification. Because the language of claims is different from language used elsewhere in the patent application or in non-patent text, this has been challenging for computer based natural language processing. We test two new LLM-based approaches and find that both provide substantially better performance than previously published values. The ability to match dense information from one domain against much more distributed information expressed in a different vocabulary may also be useful beyond the intellectual property space.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 6 references that are in the map. First posted on arXiv 14 Jul 2024.
Builds on
4 of 6 references.
References · 4
- 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
- 2023Large Language Models are Effective Text Rankers with Pairwise Ranking Promptingcited by 307
- 2020PatentMatch: A Dataset for Matching Patent Claims & Prior Artcited by 15
- 2020A Text-Embedding-based Approach to Measure Patent-to-Patent Technological Similarity -- Workflow, Code, and Applicationscited by 8
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Citing papers per year: 2025: 1.
1 paper.