Skip to content

How is TransformerFAM different from Landmark Attention?  #15

@Rock-Anderson

Description

@Rock-Anderson

Not exactly an issue (please feel free to close it), but wanted to get the authors opinion on the new TransformerFAM paper and how it is different from Landmark Attention.

My original understanding is that by introducing Landmark tokens at the end of blocks, we could potentially scale of infinite length sequences.
But the above paper just concludes - "However, in those papers, the information was not propagated infinitely", in reference to Landmark Attention.

Can the authors / someone please clarify what modifications can Landmark Attention have to achieve what T-FAM paper proposes?
Thanks.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions