this post was submitted on 27 Nov 2023
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Machine Learning
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I haven't watch the talk, but I think the reading list should have some love for SSM. (S4, S5, H3): on one hand their variants are very prominent on long range arena on other they are relatively "unknown".
They are not unknown to researchers seeing how many variants there are, but there are hundreds more videos and blogs explaining transformers. If you find a course about LLM, it will likely include Transformers but not SSM, so I think their success in LRA and absence in learning materials qualifies them for "dive in deeper" list.