Papers with patent applications
Towards Comprehensive Patent Approval Predictions:Beyond Traditional Document Classification (2022.acl-long)
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| Challenge: | a new framework for patent approval prediction is proposed to address this problem . novelty scores are based on comparing an application with millions of prior arts . |
| Approach: | They propose a framework that unifies the document classifier with handcrafted features, particularly time-dependent novelty scores. |
| Outcome: | The proposed framework unifies the document classifier with handcrafted features, particularly time-dependent novelty scores. |
Enriching Patent Claim Generation with European Patent Dataset (2025.findings-emnlp)
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| Challenge: | Existing work on large language models to assist inventors in writing patent claims relies on datasets from the United States Patent and Trademark Office. |
| Approach: | They propose a European patent dataset that provides rich textual data and structured metadata to support multiple patent-related tasks. |
| Outcome: | The proposed dataset outperforms existing datasets and GPT-4o in claim quality and cross-domain generalization. |
PAP2PAT: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs (2025.findings-acl)
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| Challenge: | In patents, the description constitutes more than 90% of the document on average, yet its automatic generation remains understudied. |
| Approach: | They propose a method to generate patent documents using a research paper as an invention specification. |
| Outcome: | The proposed model can generate 1.8k patent-paper pairs describing the same inventions, but it's difficult to provide the level of detail required. |
DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding (2025.findings-emnlp)
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| Challenge: | patent images often lack comprehensive visual context and semantic information, authors say . recent advances in vision-language models offer promising opportunities for patent analysis . |
| Approach: | They develop a framework for design patent analysis using large-scale patent dataset . they validate the effectiveness of DesignCLIP across various downstream tasks . |
| Outcome: | The proposed framework outperforms baseline and SOTA models on all tasks. |
JaParaPat: A Large-Scale Japanese-English Parallel Patent Application Corpus (2024.lrec-main)
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| Challenge: | a recent study has demonstrated that patent translation accuracy improves as the amount of training data or the number of model parameters increases. |
| Approach: | They construct a bilingual corpus of Japanese-English patent application data from 2000 to 2021 . they extracted 1.4M Japanese- English document pairs and extracted 350M sentence pairs . |
| Outcome: | The proposed method improves translation accuracy by 20 bleu points . it is the first publicly available large-scale Japanese-English patent corpus . |