2 citations · 2 across the 4 of their papers we have counts for
6 papers
When Repeated Measurements Hurt Tabular Foundation Models
Yixiang Liu, Ruizhe Deng, Bibhas Chakraborty +2
Tabular foundation models (TFMs) achieve state-of-the-art performance on IID benchmarks, but how do they respond to repeated measurements at the same inputs? Across six TFMs, synth…
Architecture Alignment With Sparse Priors in Tabular Foundation Models
Tianqi Zhao, Tianyi Zhuang, Shuo Duan +3
Tabular foundation models (TFMs) are increasingly popular because they deliver strong predictions on new datasets through in-context learning, without task-specific training or ext…
PFN-TS: Thompson Sampling for Contextual Bandits via Prior-Data Fitted Networks
Yan Shuo Tan, Kenyon Ng, Ruizhe Deng +3
Thompson sampling is a widely used strategy for contextual bandits: at each round, it samples a reward function from a Bayesian posterior and acts greedily under that sample. Prior…
TabClustPFN: A Prior-data Fitted Network for Tabular Data Clustering
Tianqi Zhao, Guanyang Wang, Yan Shuo Tan +1
Prior-data Fitted Networks (PFNs) have reframed supervised tabular learning as single-pass in-context inference without per-dataset optimization. Extending this paradigm to cluster…
See-in-Pairs: Reference Image-Guided Comparative Vision-Language Models for Medical Diagnosis
Ruinan Jin, Gexin Huang, Xinwei Shen +3
Medical image diagnosis is challenging because many diseases resemble normal anatomy and exhibit substantial interpatient variability. Clinicians routinely rely on comparative diag…
TabPFN: One Model to Rule Them All?
Qiong Zhang, Yan Shuo Tan, Qinglong Tian +1
Hollmann et al. (Nature 637 (2025) 319-326) recently introduced TabPFN, a transformer-based deep learning model for regression and classification on tabular data, which they claim…