ALFRED

A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

Mohit Shridhar Jesse Thomason Daniel Gordon Yonatan Bisk
Winson Han Roozbeh Mottaghi Luke Zettlemoyer Dieter Fox

ALFRED (Action Learning From Realistic Environments and Directives), is a new benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. Long composition rollouts with non-reversible state changes are among the phenomena we include to shrink the gap between research benchmarks and real-world applications.

Read our paper on ArXiv»

@Unpublished{ALFRED,
  title={{ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks}},
  author={Mohit Shridhar and Jesse Thomason and Daniel Gordon and Yonatan Bisk and Winson Han and Roozbeh Mottaghi and Luke Zettlemoyer and Dieter Fox},
  year={2019},
}