它能否匹配？风险投资领域自主法律代理的探索之路

摘要

在风险投资融资轮次结束前，律师开展的尽职调查包括股权结构表核对：即验证每项证券（如股份、期权、权证）及发行条款（如归属时间表、加速触发条件、转让限制）是否均有大量底层法律文件支持。尽管大语言模型在法律基准测试上持续进步，但诸如股权核对这类专业法律工作流程，即便对先进的智能体系统而言仍难以实现。该任务需要多文档推理能力、严格的证据可追溯性以及确定性输出，而现有技术方案均无法稳定满足这些要求。我们将股权结构表核对界定为法律AI现实应用场景的基准测试案例，分析比较现有智能体系统的表现，并提出一种面向核对自动化的世界模型架构——该架构更广泛地可作为应用型法律智能的基础框架。

English

Before closing venture capital financing rounds, lawyers conduct diligence that includes tying out the capitalization table: verifying that every security (for example, shares, options, warrants) and issuance term (for example, vesting schedules, acceleration triggers, transfer restrictions) is supported by large sets of underlying legal documentation. While LLMs continue to improve on legal benchmarks, specialized legal workflows, such as capitalization tie-out, remain out of reach even for strong agentic systems. The task requires multi-document reasoning, strict evidence traceability, and deterministic outputs that current approaches fail to reliably deliver. We characterize capitalization tie-out as an instance of a real-world benchmark for legal AI, analyze and compare the performance of existing agentic systems, and propose a world model architecture toward tie-out automation-and more broadly as a foundation for applied legal intelligence.

它能否匹配？风险投资领域自主法律代理的探索之路

Does It Tie Out? Towards Autonomous Legal Agents in Venture Capital

摘要

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