activity
20232026
most citedDROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2026

Robust Player-Conditional Champion Ranking for League of Legends: Style Similarity, Mastery Priors, and Archetype-Constrained Discovery

Min Heo, Pranav Kadiyam, Prasun Panthi

Champion recommendation in multiplayer online battle arena games is usually framed informally as a problem of metagame strength, personal comfort, or global win rate. We formalize…

cs.RO2025

Subtask-Aware Visual Reward Learning from Segmented Demonstrations

Changyeon Kim, Minho Heo, Doohyun Lee +4

Reinforcement Learning (RL) agents have demonstrated their potential across various robotic tasks. However, they still heavily rely on human-engineered reward functions, requiring…

cs.RO2024

EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data

Jesse Zhang, Minho Heo, Zuxin Liu +4

Most reinforcement learning (RL) methods focus on learning optimal policies over low-level action spaces. While these methods can perform well in their training environments, they…

cs.RO2024★ 3 cited

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Alexander Khazatsky, Karl Pertsch, Suraj Nair +98

The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…

cs.RO2023★ 2 cited

FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation

Minho Heo, Youngwoon Lee, Doohyun Lee +1

Reinforcement learning (RL), imitation learning (IL), and task and motion planning (TAMP) have demonstrated impressive performance across various robotic manipulation tasks. Howeve…