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An Interactive Agent Foundation Model
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Bidipta Sarkar
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2026-03-05 16:54:55
raw text
An Interactive Agent Foundation Model An Interactive Agent Foundation Model Zane Durante Bidipta Sarkar Ran Gong Rohan Taori Yusuke Noda Paul Tang Ehsan Adeli Shrinidhi Kowshika Lakshmikanth Kevin Schulman Arnold Milstein Demetri Terzopoulos Ade Famoti Noboru Kuno Ashley Llorens Hoi Vo Katsu Ikeuchi Li Fei-Fei Jianfeng Gao Naoki Wake Qiuyuan Huang Paper Model (Coming Soon!) Abstract The development of artificial intelligence systems is transitioning from creating static, task-specific models to dynamic, agent-based systems capable of performing well in a wide range of applications. We propose an Interactive Agent Foundation Model that uses a novel multi-task agent training paradigm for training AI agents across a wide range of domains, datasets, and tasks. Our training paradigm unifies diverse pre-training strategies, including visual masked auto-encoders, language modeling, and next-action prediction, enabling a versatile and adapta...
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