Earlier quoted context omitted.
As someone who is in the field: papers proposing to solve the context length problem come out every month. Almost none of the solutions stick or work as well as a dense or mostly dense model. You'll know when the problem is solved when model after consistently use a method. Until then (and especially if you're not in the field as a researcher), assume that every paper claiming to tackle context length is simply a nic…
What about Meta’s megabyte? Also nice proposal?
Just to name a few families of approaches: Sparse Attention, Hierachical Attention, Global-Local Attention,Sliding Window Attention, Locality sensitive hashing Attention, State space model, EMA gated attention.