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Exactly what I had in mind. After generating a few wrong tokens perhaps the model could realize it leads to a low probability path and have a way to "go back",
by radarsat1 1y ago
Exactly what I had in mind. After generating a few wrong tokens perhaps the model could realize it leads to a low probability path and have a way to "go back", while staying in context. Parent is right though that thinking models can kind of do that without some special token, I hadn't thought about that, nice observation.
- namibj 1y agoJust wanna remind that transformers are devoid of any "ordering/sequence" concept until you feed one in via positional encoding. It'd be easy to flag retracted tokens as such (e.g. pointing an input token one direction or the opposite similar to how RoPE encodes into directional modulation/wobble) but otherwise represent the malleable edit state with the positional encoding and accept overlap (just probably make sure autoregressive decoding/casual self attention makes it so the tokens are sufficiently able to interact preferentially with their immediate neighbors _of the same attempt/edit-revision_).