1 citations · 2 across the 5 of their papers we have counts for
5 papers
PnPXAI: A Universal XAI Framework Providing Automatic Explanations Across Diverse Modalities and Models
Seongun Kim, Sol A Kim, Geonhyeong Kim +5
Recently, post hoc explanation methods have emerged to enhance model transparency by attributing model outputs to input features. However, these methods face challenges due to thei…
Explaining the Decisions of Deep Policy Networks for Robotic Manipulations
Seongun Kim, Jaesik Choi
Deep policy networks enable robots to learn behaviors to solve various real-world complex tasks in an end-to-end fashion. However, they lack transparency to provide the reasons of…
Refining Diffusion Planner for Reliable Behavior Synthesis by Automatic Detection of Infeasible Plans
Kyowoon Lee, Seongun Kim, Jaesik Choi
Diffusion-based planning has shown promising results in long-horizon, sparse-reward tasks by training trajectory diffusion models and conditioning the sampled trajectories using au…
Variational Curriculum Reinforcement Learning for Unsupervised Discovery of Skills
Seongun Kim, Kyowoon Lee, Jaesik Choi
Mutual information-based reinforcement learning (RL) has been proposed as a promising framework for retrieving complex skills autonomously without a task-oriented reward function t…
Enabling AI Quality Control via Feature Hierarchical Edge Inference
Jinhyuk Choi, Seong-Lyun Kim, Seung-Woo Ko
With the rise of edge computing, various AI services are expected to be available at a mobile side through the inference based on deep neural network (DNN) operated at the network…