6 papers
The Imitator Game: Benchmarking Robot Imitative Ability Beyond Action Prediction
Xunzhe Zhou, Yiyang Cai, Fengyi Wang +9
Humans imitate at the level of intent: given a demonstration, we infer its goal and carry it out with whatever tools, objects, and layouts are at hand. Current robot policies inste…
DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation
Yunchao Yao, Zhuxiu Xu, Tianqi Zhang +12
Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sen…
DexHoldem: An Agentic Robotics Benchmark for Dexterous Manipulation in Texas Hold'em
Feng Chen, Tianzhe Chu, Li Sun +6
Evaluating embodied systems with real dexterous hardware requires more than isolated motor-skill tests: an agent must perceive a changing scene (e.g. a tabletop), choose a context-…
DeTrack: A Benchmark and Altitude-Aware Dual World Model for Drone-embodied Tracking
Guyue Hu, Haoming Liu, Siyuan Song +3
Aerial object tracking has broad applications in public safety, emergency rescue, wildlife monitoring, and related fields. However, existing aerial tracking benchmarks are mainly b…
HyperTASR: Hypernetwork-Driven Task-Aware Scene Representations for Robust Manipulation
Li Sun, Jiefeng Wu, Feng Chen +2
Effective policy learning for robotic manipulation requires scene representations that selectively capture task-relevant environmental features. Current approaches typically employ…
On the Evaluation of Generative Robotic Simulations
Feng Chen, Botian Xu, Pu Hua +4
Due to the difficulty of acquiring extensive real-world data, robot simulation has become crucial for parallel training and sim-to-real transfer, highlighting the importance of sca…