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Podcast: Arxiv Papers
Episode: Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data
Description: Real-TabPFN enhances tabular data performance by continued pre-training on curated real-world datasets, outperforming models trained on broader datasets, achieving significant gains on 29 OpenML AutoML Benchmark datasets.https://arxiv.org/abs//2507.03971YouTube: https://www.youtube.com/@ArxivPapersTikTok: https://www.tiktok.com/@arxiv_papersApple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers