mlsanityData to 7 Oct 2026

Pat-DEVAL: Chain-of-Legal-Thought Evaluation for Patent Description

arXiv 2601.00166 ↗First posted 1 Jan 2026cs.CLcited by 3

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Abstract (arXiv)

Patent descriptions must deliver comprehensive technical disclosure while meeting strict legal standards such as enablement and written description requirements. Although large language models have enabled end-to-end automated patent drafting, existing evaluation approaches fail to assess long-form structural coherence and statutory compliance specific to descriptions. We propose Pat-DEVAL, the first multi-dimensional evaluation framework dedicated to patent description bodies. Leveraging the LLM-as-a-judge paradigm, Pat-DEVAL introduces Chain-of-Legal-Thought (CoLT), a legally-constrained reasoning mechanism that enforces sequential patent-law-specific analysis. Experiments validated by patent expert on our Pap2Pat-EvalGold dataset demonstrate that Pat-DEVAL achieves a Pearson correlation of 0.69, significantly outperforming baseline metrics and existing LLM evaluators. Notably, the framework exhibits a superior correlation of 0.73 in Legal-Professional Compliance, proving that the explicit injection of statutory constraints is essential for capturing nuanced legal validity. By establishing a new standard for ensuring both technical soundness and legal compliance, Pat-DEVAL provides a robust methodological foundation for the practical deployment of automated patent drafting systems.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 7 of its 22 references that are in the map. First posted on arXiv 1 Jan 2026.

Builds on

7 of 22 references.

References · 7

  1. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,462
  2. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,205
  3. 2020Big Bird: Transformers for Longer Sequencescited by 1,673
  4. 2019PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarizationcited by 1,100
  5. 2019Patent Claim Generation by Fine-Tuning OpenAI GPT-2cited by 49
  6. 2025PatentScore: Multi-dimensional Evaluation of LLM-Generated Patent Claimscited by 10
  7. 2024Pap2Pat: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairscited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

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  1. 2026When Reasoning Hurts Legal Drafting: The Verbalization Bottleneck in Patent Claim Generation
  2. 2025PatentMind: A Multi-Aspect Reasoning Graph for Patent Similarity Evaluation
  3. 2025PEDANTIC: A Dataset for the Automatic Examination of Definiteness in Patent Claims
  4. 2025PATENTWRITER: A Benchmarking Study for Patent Drafting with LLMs
  5. 2026PILOT-Bench: A Benchmark for Legal Reasoning in the Patent Domain with IRAC-Aligned Classification Tasks
  6. 2025Self-Filtered Distillation with LLMs-generated Trust Indicators for Reliable Patent Classification
  7. 2024IPEval: A Bilingual Intellectual Property Agency Consultation Evaluation Benchmark for Large Language Models
  8. 2025ToC: Tree-of-Claims Search with Multi-Agent Language Models