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cs.LG2026★ 1 cited
Interpretable Tabular Foundation Models via In-Context Kernel Regression
Ratmir Miftachov, Bruno Charron, Simon Valentin
Tabular foundation models like TabPFN and TabICL achieve state-of-the-art performance through in-context learning, yet their architectures remain fundamentally opaque. We introduce…
cs.LG2020★ 8 cited
PiRank: Scalable Learning To Rank via Differentiable Sorting
Robin Swezey, Aditya Grover, Bruno Charron +1
A key challenge with machine learning approaches for ranking is the gap between the performance metrics of interest and the surrogate loss functions that can be optimized with grad…