๐ŸŽ“How I Study AIHISA
๐Ÿ“–Read
๐Ÿ“„Papers๐Ÿ“ฐBlogs๐ŸŽฌCourses
๐Ÿ’กLearn
๐Ÿ›ค๏ธPaths๐Ÿ“šTopics๐Ÿ’กConcepts๐ŸŽดShorts
๐ŸŽฏPractice
๐Ÿ“Daily Log๐ŸŽฏPrompts๐Ÿง Review
SearchSettings
How I Study AI - Learn AI Papers & Lectures the Easy Way

Papers2

AllBeginnerIntermediateAdvanced
All SourcesarXiv
#Compositionality

PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding

Beginner
Panagiotis Koromilas, Andreas D. Demou et al.Feb 1arXiv

PolySAE is a new kind of sparse autoencoder that keeps a simple, linear way to find features but uses a smarter decoder that can multiply features together.

#Sparse Autoencoder#Polynomial Decoder#Feature Interactions

Not triaged yet

When Reasoning Meets Its Laws

Intermediate
Junyu Zhang, Yifan Sun et al.Dec 19arXiv

The paper proposes the Laws of Reasoning (LORE), simple rules that say how much a model should think and how accurate it can be as problems get harder.

#Large Reasoning Models#Laws of Reasoning#Compute Law

Not triaged yet