| Challenge: | Patent-CR is the first dataset created for the patent claim revision task in English. |
| Approach: | They propose to create a dataset for the patent claim revision task in English that includes both initial patent applications rejected by examiners and the final granted versions. |
| Outcome: | The proposed dataset includes both initial patent applications rejected by examiners and the final granted versions. |
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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. |
Patentformer: A Novel Method to Automate the Generation of Patent Applications (2024.emnlp-industry)
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| 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. |
Can Large Language Models Generate High-quality Patent Claims? (2025.findings-naacl)
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| Challenge: | Large language models (LLMs) have shown exceptional performance across various text generation tasks, but remain under-explored in the patent domain, which offers highly structured and precise language. |
| Approach: | They construct a dataset to investigate the performance of current LLMs in patent claim generation. |
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PatentEval: Understanding Errors in Patent Generation (2024.naacl-long)
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| Challenge: | a patent is a legal instrument that grants inventors or entities exclusive rights over their invention for a designated period. |
| Approach: | They propose a typology specifically designed for evaluating two distinct tasks in machine-generated patent texts. |
| Outcome: | The proposed approach provides valuable insights into the capabilities and limitations of current language models in the specialized field of patent text generation. |
PatentScore: Multi-dimensional Evaluation of LLM-Generated Patent Claims (2025.emnlp-main)
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| Challenge: | Existing natural language generation (NLG) metrics fail to capture domain-specific nuances . patent claims require precise assessment of structural elements such as antecedent consistency and claim dependency. |
| Approach: | They propose a multi-dimensional evaluation framework specifically designed for patent claims . PatentScore integrates hierarchical decomposition of claim elements, validation patterns and scoring across structural, semantic, and legal dimensions. |
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Towards Better Evaluation for Generated Patent Claims (2025.acl-long)
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| Challenge: | Existing studies highlight inconsistencies between automated evaluation metrics and human expert assessments for patent claims. |
| Approach: | They propose a multi-dimensional evaluation method specifically designed for patent claims that incorporates features annotated by patent experts. |
| Outcome: | The proposed method achieves highest correlation with human expert evaluations across all assessment criteria across all tested metrics. |
Claim Verification in the Age of Large Language Models: A Survey (2026.acl-srw)
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| Challenge: | Recent election cycles have seen a large number of false information spread across social media and news platforms. |
| Approach: | They propose a framework for automated claim verification using Large Language Models and Retrieval Augmented Generation. |
| Outcome: | The proposed frameworks are based on large-scale models and new methods such as Retrieval Augmented Generation (RAG). |
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. |
A Systematic Survey of Claim Verification: Corpora, Systems, and Case Studies (2025.findings-emnlp)
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| Challenge: | This survey analyses 198 studies published between January 2022 and March 2025 . |
| Approach: | This survey synthesizes recent advances in CV corpus creation and system design. |
| Outcome: | The results of this study are synthesized from 198 studies published between January 2022 and March 2025. |
A Survey on Patent Analysis: From NLP to Multimodal AI (2025.acl-long)
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| Challenge: | Recent advances in pretrained language models and large language models have demonstrated transformative capabilities across diverse domains. |
| Approach: | They propose a taxonomy for categorization based on tasks in the patent life cycle . they introduce a novel taxonomies for categorizing based upon tasks in patent life cycles . |
| Outcome: | The proposed method is based on tasks in the patent life cycle and provides a taxonomy for categorization based upon tasks in patent life cycles. |