Papers with USPTO
Structural Patent Classification Using Label Hierarchy Optimization (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods for patent classification ignore key technical content claims and citation relationships . existing methods treat labels as independent targets, failing to exploit semantic and structural information within the label taxonomy. |
| Approach: | They propose a Claim Structure based Patent Classification model with Label Awareness . structural graph learning is used to mine the internal logic of patent claims . |
| Outcome: | The proposed method is more effective than state-of-the-art classification models. |
Patentformer: A Novel Method to Automate the Generation of Patent Applications (2024.emnlp-industry)
Copied to clipboard
| Challenge: | Patentformer is a novel method for generating patent specification by fine-tuning the generative models with diverse sources of information, e.g., patent claims, drawing text, and brief descriptions of the drawings. |
| Approach: | They propose a method for generating patent specification by fine-tuning generative models with diverse sources of information, e.g., patent claims, drawing text, and brief descriptions of the drawings. |
| Outcome: | The proposed method generates patent specification in legal writing style and human-like quality may be better than the actual specification. |
Rethinking NLP for Chemistry: A Critical Look at the USPTO Benchmark (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Natural Language Processing (NLP) has revolutionized computer-aided synthesis planning by reframing chemical synthesis prediction as a sequence-to-sequence modeling problem over molecular string representations like SMILES. |
| Approach: | They propose to reframe chemical synthesis prediction as a sequence-to-sequence modeling problem over molecular string representations like SMILES. |
| Outcome: | The proposed framework yields impressive benchmark scores on the USPTO dataset, a large corpus of reactions extracted from US patents. |