Papers
arxiv:2512.10071

Openpi Comet: Competition Solution For 2025 BEHAVIOR Challenge

Published on Dec 10
ยท Submitted by
Delin Qu
on Dec 16
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Abstract

A solution for the 2025 BEHAVIOR Challenge in everyday household tasks using pre-training and post-training techniques substantially outperforms other submissions.

AI-generated summary

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 ฯ€_{0.5}, we focus on systematically building our solution by studying the effects of training techniques and data. Through careful ablations, we show the scaling power in pre-training and post-training phases for competitive 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.

Community

Paper author Paper submitter

OpenPi Comet is the submission of Team Comet for the 2025 BEHAVIOR Challenge. We provides a unified framework for pre-training, post-training, data generation and evaluation of ฯ€0.5 (Pi05) models on BEHAVIOR-1K.

๐Ÿ“„ Arxiv: https://arxiv.org/pdf/2512.10071
๐Ÿค— Code: https://github.com/mli0603/openpi-comet
๐Ÿ“ Blog: https://lnkd.in/gSv2K5ua

Below are 8 representative tasks that showcase some of the most interesting results from our system.

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