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Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts
Chao Peter Yang, Cynthia Rudin, Yue Jiang +2
Deep learning has transformed symbolic music generation by borrowing the training paradigms of large language models, with systems such as NotaGen now producing complete, stylistic…
Falling Trees: A Model Class for Interpretable Risk Prioritization
Varun Babbar, Zachery Boner, Margo Seltzer +1
Many real-world decisions require prioritizing high-risk cases, such as clinicians prioritizing high-risk patients before lower-risk ones. Falling rule lists (FRLs), which are orde…
Learning Metamaterial Eigenmodes with Wavelet-Encoded Fourier Neural Operators
Han Zhang, Alexander Ogren, Cynthia Rudin +2
Machine learning surrogates based on neural operators have shown broad applicability in solving forward PDE problems. However, eigenvalue problems, in which an eigenparameter and o…
ArborEnum: Decision Tree Rashomon Sets over Continuous Features
Zakk Heile, Hayden McTavish, Margo Seltzer +1
The Rashomon effect describes the phenomenon that many models can achieve nearly equivalent performance on the same learning task, with significant ramifications for robustness, fe…
Do Judges Behave Like Algorithms?
Riya Manchanda, Eric Chen, Chloe Zhu +3
What if judges already behave like algorithms? As artificial intelligence and algorithms are deployed in many settings, including the judicial system, many have debated whether jud…
Position: Explainability Research Must Prioritize Foundations over Ad-hoc Methods
Michal Moshkovitz, Suraj Srinivas, Lesia Semenova +7
Despite the proliferation of Explainable AI (XAI) techniques -- from feature attributions to sparse autoencoders -- explanations rarely influence real-world workflows. In practice,…