VynFi/vynfi-journal-entries-10m

研究规模的合成总账数据集。包含约1090万条日记账分录行，模拟一家10公司跨国企业的财务数据，由DataSynth v5.29.0生成，采用完整的SOTA-N结构保真度轮次和中心集中抽象（ConcentrationPipeline，#143）。作为[`VynFi/vynfi-journal-entries-1m`](https://huggingface.co/datasets/VynFi/vynfi-journal-entries-1m)的伴随数据集（使用相同的生成器、杠杆堆栈、欺诈类型和异常类型列），但规模约为10倍，适用于行为保真度研究、大规模图神经网络训练，以及与学习型表格生成器（如CTGAN、TVAE、GaussianCopula、TabularARGN）的直接基准测试。

Research-scale synthetic GL dataset. ~10.9 M journal-entry lines from a 10-company multinational, generated by DataSynth v5.29.0 with the full SOTA-N structural-fidelity round + the central concentration abstraction (`ConcentrationPipeline`, #143). Companion to [`VynFi/vynfi-journal-entries-1m`](https://huggingface.co/datasets/VynFi/vynfi-journal-entries-1m) (same generator, same lever stack, same fraud-typology + anomaly-type columns) but ~10× scale, for behavioural-fidelity research, GNN training at scale, and head-to-head benchmarks against learned tabular generators (CTGAN / TVAE / GaussianCopula / TabularARGN).