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cs.LG2026
Structural Disentanglement in Bilinear MLPs via Architectural Inductive Bias
Ojasva Nema, Kaustubh Sharma, Aditya Chauhan +1
Selective unlearning and long-horizon extrapolation remain fragile in modern neural networks, even when tasks have underlying algebraic structure. In this work, we argue that these…
cs.LG2026
Mechanistic Evidence for Spectral Structures in Prior-Data Fitted Networks
Kaustubh Sharma, Srijan Tiwari, Ojasva Nema +1
Prior-Data Fitted Networks (PFNs) perform approximate Bayesian inference in a single forward pass, and tabular foundation models (TFMs) built on them are now widely used. To unders…
cs.LG2025
Decoupled-Value Attention for Prior-Data Fitted Networks: GP Inference for Physical Equations
Kaustubh Sharma, Simardeep Singh, Parikshit Pareek
Prior-data fitted networks (PFNs) are a promising alternative to time-consuming Gaussian process (GP) inference for creating fast surrogates of physical systems. PFN reduces the co…