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Found 2 papers, 2 papers with code
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
State-space models (SSMs), such as Mamba (Gu & Dao, 2023), have been proposed as alternatives to Transformer networks in language modeling, by incorporating gating, convolutions, and input-dependent token selection to mitigate the quadratic cost of multi-head attention.
Image Clustering Conditioned on Text Criteria
Classical clustering methods do not provide users with direct control of the clustering results, and the clustering results may not be consistent with the relevant criterion that a user has in mind.
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