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Kyle Erwin

2 accepted papers

2025

Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations

AAAI 2025technical

Recent advances in machine learning have led to a surge in adoption of neural networks for various tasks, but lack of interpretability remains an issue for many others in which an understanding of the features influencing the prediction is necessary to ensure fairness, safety, and legal compliance.…

2023

Self-Supervised Rule Learning to Link Text Segments to Relational Elements of Structured Knowledge

EMNLP 2023long findings

We present a neuro-symbolic approach to self-learn rules that serve as interpretable knowledge to perform relation linking in knowledge base question answering systems. These rules define natural language text predicates as a weighted mixture of knowledge base paths. The weights learned during train…

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