2 papers
cs.LG2026
TabPFN Through The Looking Glass: An interpretability study of TabPFN and its internal representations
Aviral Gupta, Armaan Sethi, Dhruv Kumar
Tabular foundational models are pre-trained models designed for a wide range of tabular data tasks. They have shown strong performance across domains, yet their internal representa…
cs.LG2025
No Training Wheels: Steering Vectors for Bias Correction at Inference Time
Aviral Gupta, Armaan Sethi, Ameesh Sethi
Neural network classifiers trained on datasets with uneven group representation often inherit class biases and learn spurious correlations. These models may perform well on average…