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Openpi Comet: Competition Solution For 2025 BEHAVIOR Challenge

Junjie Bai
Yu-Wei Chao
Qizhi Chen
Jinwei Gu
Moo Jin Kim
Zhaoshuo Li
Xuan Li
Tsung-Yi Lin
Ming-Yu Liu
Nic Ma
Kaichun Mo
Delin Qu
Shangkun Sun
Hongchi Xia
Fangyin Wei
Xiaohui Zeng
Main:7 Pages
5 Figures
Bibliography:2 Pages
4 Tables
Abstract

The 2025 BEHAVIOR Challenge is designed to rigorously track progress toward solving long-horizon tasks by physical agents in simulated environments. BEHAVIOR-1K focuses on everyday household tasks that people most want robots to assist with and these tasks introduce long-horizon mobile manipulation challenges in realistic settings, bridging the gap between current research and real-world, human-centric applications. This report presents our solution to the 2025 BEHAVIOR Challenge in a very close 2nd place and substantially outperforms the rest of the submissions. Building on π0.5\pi_{0.5}, we focus on systematically building our solution by studying the effects of training techniques and data. Through careful ablation studies, we reveal the scaling benefits in both the pre-training and post-training phases, leading to a validation Q-score of 0.345, significantly surpassing previous state-of-the-art performance. We summarize our practical lessons and design recommendations that we hope will provide actionable insights for the broader embodied AI community when adapting powerful foundation models to complex embodied scenarios. Project page:this https URL

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