and each trajectory in multimodal memory. We first use
the text encoder of CLIP model to compute the embedding
of the query and task key of each entry in memory. We
select the memory entries with similarity higher than the
confidence threshold as the candidate entries. Then we will
compute the visual state embedding of query and states in
candidate entires. Then we sort the candidate entries with
the visual embedding similarities, which can be formed as:
JARVIS-1