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AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation
Stephen Ni-Hahn, Rico Zhu, Jerry Yin +3
Hierarchical representations provide powerful and principled approaches for analyzing many musical genres. Such representations have been broadly studied in music theory, for insta…
NodMAISI: Nodule-Oriented Medical AI for Synthetic Imaging
Fakrul Islam Tushar, Ehsan Samei, Cynthia Rudin +1
Objective: Although medical imaging datasets are increasingly available, abnormal and annotation-intensive findings critical to lung cancer screening, particularly small pulmonary…
What You See is (Usually) What You Get: Multimodal Prototype Networks that Abstain from Expensive Modalities
Muchang Bahng, Charlie Berens, Jon Donnelly +3
Species detection is important for monitoring the health of ecosystems and identifying invasive species, serving a crucial role in guiding conservation efforts. Multimodal neural n…
It's LIT! Reliability-Optimized LLMs with Inspectable Tools
Ruixin Zhang, Jon Donnelly, Zhicheng Guo +4
Large language models (LLMs) have exhibited remarkable capabilities across various domains. The ability to call external tools further expands their capability to handle real-world…
This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN
Dennis Tang, Jon Donnelly, Alina Jade Barnett +8
The presence of interictal epileptiform discharges (IEDs) in electroencephalogram (EEG) recordings is a critical biomarker of epilepsy. Even trained neurologists find detecting IED…
ProGress: Structured Music Generation via Graph Diffusion and Hierarchical Music Analysis
Stephen Ni-Hahn, Chao Péter Yang, Mingchen Ma +3
Artificial Intelligence (AI) for music generation is undergoing rapid developments, with recent symbolic models leveraging sophisticated deep learning and diffusion model algorithm…