vessels-source
收藏资源简介：
Vessels — Source Mirror数据集是GitHub仓库szl-holdings/vessels在Hugging Face平台上的源代码镜像。该仓库是SZL Holdings研究堆栈的一部分，旨在为受SZL治理的AI代理提供一个容器编排基础层。核心功能包括代理实例的生命周期管理、边界强制执行，并为符合Λ-compliant规范的代理实例生成SLSA（软件供应链级别保障）认证的部署凭证。数据集内容包含源代码文件，并非用于机器学习的训练数据；它是一个在2026-05-29提交点的静态快照，用于提高项目的可发现性，其规范源代码仍位于GitHub主仓库。该数据集与SZL Holdings的其他研究成果紧密关联，如形式化验证论文、对齐模型、可观测性数据等。所有代码声明均可追溯至Zenodo DOI、GitHub提交哈希，并在适用情况下关联基于Mathlib v4.13.0的Lean 4形式化证明。数据集规模小于1K，语言为英文。
The Vessels — Source Mirror dataset is a source code mirror of the GitHub repository szl-holdings/vessels on the Hugging Face platform. This repository is part of the SZL Holdings research stack, designed to provide a container orchestration base layer for AI agents governed by SZL. Its core functions include lifecycle management of agent instances, boundary enforcement, and generating SLSA (Software Supply Chain Levels for Artifacts) certified deployment credentials for Λ-compliant agent instances. The dataset content consists of source code files and is not intended for machine learning training data; it is a static snapshot at a specific commit point (2026-05-29) to enhance project discoverability, with the canonical source code remaining in the main GitHub repository. The dataset is closely linked to other SZL Holdings research outputs, such as formal verification papers, alignment models, and observability data. All code claims are traceable to Zenodo DOIs, GitHub commit hashes, and, where applicable, linked to Lean 4 formal proofs based on Mathlib v4.13.0. The dataset size is less than 1K, and the language is English.
数据集概述
数据集名称：vessels — Maritime Fleet Intelligence Source
许可证：Apache 2.0
语言：英文
规模：n < 1K（小于1000条记录）
任务类别：其他（other）
标签：海事、制裁、船舶追踪、暗船检测、治理、人工智能治理、智能体人工智能
核心能力
该数据集支持以下四项海事舰队情报分析能力：
| 能力 | 描述 |
|---|---|
| 制裁筛查 | 实时船舶制裁名单交叉核对 |
| 暗船检测 | 基于AIS信号缺失分析与行为特征的暗船识别 |
| 所有权图谱 | 多跳受益所有权解析 |
| 航程分析 | 港口停靠模式与航线异常检测 |
相关链接
- 组织卡片：https://huggingface.co/datasets/SZLHOLDINGS/SZLHOLDINGS
- 源代码仓库：https://github.com/szl-holdings/vessels
引用信息
如需引用该数据集，请使用以下BibTeX格式：
@misc{lutar2026ouroboros, title = {Ouroboros: Formal Verification of Agentic AI Governance — v18.0}, author = {Lutar, Stephen P.}, year = {2026}, doi = {10.5281/zenodo.20434276}, url = {https://doi.org/10.5281/zenodo.20434276} }
联系方式
- 联系人：Stephen P. Lutar
- 邮箱：stephen@szlholdings.com
- ORCID：0009-0001-0110-4173
- GitHub：https://github.com/szl-holdings
- Hugging Face：https://huggingface.co/SZLHOLDINGS
