RESEARCH PAPERYear 2023

PaLM-E: An Embodied Multimodal Language Model

Danny Driess; Fei Xia; Mehdi S. M. Sajjadi; Corey Lynch; Aakanksha Chowdhery; Brian Ichter; Ayzaan Wahid; Jonathan Tompson; Quan Vuong; Tianhe Yu; Wenlong Huang; Yevgen Chebotar; Pierre Sermanet; Daniel Duckworth; Sergey Levine; Vincent Vanhoucke; Karol Hausman; Marc Toussaint; Klaus Greff; Andy Zeng; Igor Mordatch; Pete Florence

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Major category
Components of WAMs
Architecture
Not applicable
Prediction paradigm
Not applicable
Source review status
Verified from primary sources

Category review. PaLM-E supplies a reusable embodied multimodal language backbone by interleaving encoded sensor observations with text tokens. It produces text/high-level skill instructions executed by separate controllers; its component role is language/vision-language conditioning, not a complete world-action backbone. Reading evidence

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