The Transiting Exoplanet Survey Satellite (TESS) Full-Frame Images (FFIs) provide photometric time series for millions of stars, enabling transit searches beyond the limited set of pre-selected 2-minute targets. However, FFIs present additional challenges for transit identification and vetting. In this work, we apply ExoMiner++ 2.0, an adaptation of the ExoMiner++ framework originally developed for TESS 2-minute data, to FFI light curves. The model is used to perform large-scale planet versus non-planet classification of Threshold Crossing Events across the sectors analyzed in this study. We construct a uniform vetting catalog of all evaluated signals and assess model performance under different observing conditions. We find that ExoMiner++ 2.0 generalizes effectively to the FFI domain, providing robust discrimination between planetary signals, astrophysical false positives, and instrumental artifacts despite the limitations inherent to longer cadence data. This work extends the applicability of ExoMiner++ to the full TESS dataset and supports future population studies and follow-up prioritization.

翻译：凌星系外行星巡天卫星（TESS）的全帧图像（FFIs）为数百万颗恒星提供了测光时间序列，使得凌星搜索能够超越有限的预选2分钟目标集。然而，FFIs对凌星识别与审查提出了额外的挑战。在本工作中，我们将ExoMiner++ 2.0——一个最初为TESS 2分钟数据开发的ExoMiner++框架的适配版本——应用于FFI光变曲线。该模型用于对本研究分析的各观测扇区中的阈值穿越事件进行大规模的行星与非行星分类。我们构建了一个包含所有已评估信号的统一审查目录，并评估了模型在不同观测条件下的性能。我们发现，尽管存在较长采样周期数据固有的局限性，ExoMiner++ 2.0能有效地推广到FFI领域，在行星信号、天体物理假阳性以及仪器伪影之间提供稳健的区分。这项工作将ExoMiner++的适用性扩展至完整的TESS数据集，并为未来的行星群体研究和后续观测优先级排序提供支持。