activity
20242026
collaborators

5 papers

stat.ML2026

SGD Provably Prioritizes a Shortcut Spurious Feature in the XOR Model

Tyler LaBonte, Vidya Muthukumar

Neural networks are known to be susceptible to over-reliance on spurious correlations. However, the precise mechanism by which models exploit shortcut features is not fully underst…

cs.LG2026

On the Unreasonable Effectiveness of Last-layer Retraining

John C. Hill, Tyler LaBonte, Xinchen Zhang +1

Last-layer retraining (LLR) methods -- wherein the last layer of a neural network is reinitialized and retrained on a held-out set following ERM training -- have garnered interest…

cs.AI2026

Phi-4-reasoning-vision-15B Technical Report

Jyoti Aneja, Michael Harrison, Neel Joshi +3

We present Phi-4-reasoning-vision-15B, a compact open-weight multimodal reasoning model, and share the motivations, design choices, experiments, and learnings that informed its dev…

stat.ML2025

Task Shift: From Classification to Regression in Overparameterized Linear Models

Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar

Modern machine learning methods have recently demonstrated remarkable capability to generalize under task shift, where latent knowledge is transferred to a different, often more di…

cs.LG2024

The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations

Tyler LaBonte, John C. Hill, Xinchen Zhang +2

Modern machine learning models are prone to over-reliance on spurious correlations, which can often lead to poor performance on minority groups. In this paper, we identify surprisi…