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This paper introduces LogicTree-RAG, a logic tree-guided retrieval-augmented generation framework for automating long-form patent drafting, enhancing content quality and token efficiency compared to existing methods.
This paper proposes TriAdReview, a triangular adversarial review architecture that uses two independent reviewer models (engineering and boundary perspectives) and a judging mechanism to iteratively improve a generator model's output for technical document generation. Experiments show a 10.1% overall improvement over single-model baselines, with strong gains in security audit, code generation, and architecture design, but a degradation on requirements analysis indicating task-dependent effectiveness.