2 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
Bi-ICE: An Inner Interpretable Framework for Image Classification via Bi-directional Interactions between Concept and Input Embeddings
Jinyung Hong, Yearim Kim, Keun Hee Park +3
Inner interpretability is a promising field aiming to uncover the internal mechanisms of AI systems through scalable, automated methods. While significant research has been conduct…
Learning Decomposable and Debiased Representations via Attribute-Centric Information Bottlenecks
Jinyung Hong, Eun Som Jeon, Changhoon Kim +5
Biased attributes, spuriously correlated with target labels in a dataset, can problematically lead to neural networks that learn improper shortcuts for classifications and limit th…
Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship Detection
Jinyung Hong, Theodore P. Pavlic
The single-hidden-layer Randomly Weighted Feature Network (RWFN) introduced by Hong and Pavlic (2021) was developed as an alternative to neural tensor network approaches for relati…
An Insect-Inspired Randomly, Weighted Neural Network with Random Fourier Features For Neuro-Symbolic Relational Learning
Jinyung Hong, Theodore P. Pavlic
Insects, such as fruit flies and honey bees, can solve simple associative learning tasks and learn abstract concepts such as "sameness" and "difference", which is viewed as a highe…