2 papers
cs.LG2023
Concept-Centric Transformers: Enhancing Model Interpretability through Object-Centric Concept Learning within a Shared Global Workspace
Jinyung Hong, Keun Hee Park, Theodore P. Pavlic
Many interpretable AI approaches have been proposed to provide plausible explanations for a model's decision-making. However, configuring an explainable model that effectively comm…
cs.LG2020
Randomly Weighted, Untrained Neural Tensor Networks Achieve Greater Relational Expressiveness
Jinyung Hong, Theodore P. Pavlic
Neural Tensor Networks (NTNs), which are structured to encode the degree of relationship among pairs of entities, are used in Logic Tensor Networks (LTNs) to facilitate Statistical…