AI 中文总结
TabPFN-3.5 是新的旗舰表格基础模型，在 TabArena 等基准上超越前代和所有基线，支持非独立同分布、多模态及高基数数据，并提供更快推理和更强思考模式。
AI 中文摘要
我们推出了 TabPFN-3.5，这是我们新的旗舰表格基础模型。在广泛的表格问题上，它显著优于其前身 TabPFN-3 以及所有现有基线。TabPFN-3.5 在 TabArena 的标准表格预测中树立了新的最先进水平，并将其扩展到实践者遇到的数据：具有时间或分组划分的非独立同分布数据、包含字符串、文本和图像的表格、高基数分类特征以及具有许多特征的宽表。这些收益也延续到了我们的任务特定框架中：在关系数据上达到最先进水平，并提供更强的时间序列预测。为了更快的推理，我们的变体 TabPFN-3.5-Fast 运行速度比 TabPFN-3 快达 3 倍，同时保留了大部分准确性提升。此外，我们升级了 TabPFN-3.5-Plus，通过先进的文本和日期处理以及专有的推理优化扩展了我们的多模态能力。最后，我们发布了 Thinking 模式的新版本 TabPFN-3.5-Thinking，它扩展了推理时的计算量，进一步推动了最先进水平。它受益于我们更强的基座模型以及推理时的改进，使其比 TabPFN-3-Thinking 快达 12 倍。
英文摘要
We introduce TabPFN-3.5, our new flagship Tabular Foundation Model. It significantly outperforms its predecessor, TabPFN-3, and all existing baselines across a broad range of tabular problems. TabPFN-3.5 sets a new state of the art on standard tabular prediction in TabArena, and extends it to the data practitioners encounter in practice: non-i.i.d. data with temporal or grouped splits, tables with strings, text and images, high-cardinality categorical features, and wide tables with many features. These gains carry over to our task-specific harnesses: state of the art on relational data and stronger time-series forecasting. For faster inference, our variant TabPFN-3.5-Fast runs up to 3x faster than TabPFN-3 while keeping most of the accuracy gains. In addition, we upgrade TabPFN-3.5-Plus, expanding our multimodal capabilities with advanced text and date handling alongside proprietary inference optimizations. Finally, we release a new version of our Thinking mode, TabPFN-3.5-Thinking, which scales inference-time computation to push the state of the art further. It benefits from our stronger base model and from inference-time improvements that make it up to 12x faster than TabPFN-3-Thinking.
