← Search

Landon Butler

7 accepted papers

2025

Proxy-SPEX: Sample-Efficient Interpretability via Sparse Feature Interactions in LLMs

NeurIPS 2025spotlight

Large Language Models (LLMs) have achieved remarkable performance by capturing complex interactions between input features. To identify these interactions, most existing approaches require enumerating all possible combinations of features up to a given order, causing them to scale poorly with the nu…

Cited by 0SourcecodeScholar
2025

SPEX: Scaling Feature Interaction Explanations for LLMs

ICML 2025poster

Large language models (LLMs) have revolutionized machine learning due to their ability to capture complex interactions between input features. Popular post-hoc explanation methods like SHAP provide *marginal* feature attributions, while their extensions to interaction importances only scale to small…

2024

Learning to Understand: Identifying Interactions via the Möbius Transform

NeurIPS 2024poster

One of the key challenges in machine learning is to find interpretable representations of learned functions. The Möbius transform is essential for this purpose, as its coefficients correspond to unique *importance scores* for *sets of input variables*. This transform is closely related to widely use…

Cited by 3SourcePDFScholar
2024

Non Commutative Convolutional Signal Models in Neural Networks: Stability to Small Deformations

ICASSP 2024accepted

In this paper we discuss the results recently published in [1] about algebraic signal models (ASMs) based on non commutative algebras and their use in convolutional neural networks. Relying on the general tools from algebraic signal processing (ASP), we study the filtering and stability properties o…

Cited by 0SourceScholar
2021

Learning Connectivity for Data Distribution in Robot Teams

IROS 2021poster

Many algorithms for control of multi-robot teams operate under the assumption that low-latency, global state information necessary to coordinate agent actions can readily be disseminated among the team. However, in harsh environments with no existing communication infrastructure, robots must form ad…

Cited by 12SourcecodeScholar