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20212026
most citedImitation Learning: Progress, Taxonomies and Challenges

10 citations · 10 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Test-Time Scaling for World Action Models via Zero-Shot Geometric Evaluation

Zesen Zhao, Minkyoung Cho, Hui shen +4

Test-time scaling improves foundation-model inference by spending additional computation, but robot control requires deciding whether extra compute is useful before executing an ac…

cs.RO2026

DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo

Hanwen Wang, Weizhi Zhao, Xiangyu Wang +11

Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands standardized benchmarks for…

cs.RO2024

Interpretable Robotic Manipulation from Language

Boyuan Zheng, Jianlong Zhou, Fang Chen

Humans naturally employ linguistic instructions to convey knowledge, a process that proves significantly more complex for machines, especially within the context of multitask robot…

cs.NE2023

Genetic Imitation Learning by Reward Extrapolation

Boyuan Zheng, Jianlong Zhou, Fang Chen

Imitation learning demonstrates remarkable performance in various domains. However, imitation learning is also constrained by many prerequisites. The research community has done in…

cs.LG2023

Explaining Imitation Learning through Frames

Boyuan Zheng, Jianlong Zhou, Chunjie Liu +2

As one of the prevalent methods to achieve automation systems, Imitation Learning (IL) presents a promising performance in a wide range of domains. However, despite the considerabl…

cs.LG2022

GANExplainer: GAN-based Graph Neural Networks Explainer

Yiqiao Li, Jianlong Zhou, Boyuan Zheng +1

With the rapid deployment of graph neural networks (GNNs) based techniques into a wide range of applications such as link prediction, node classification, and graph classification…

cs.LG2021★ 10 cited

Imitation Learning: Progress, Taxonomies and Challenges

Boyuan Zheng, Sunny Verma, Jianlong Zhou +2

Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors. Its success has been demonstra…