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The Geometry of Concepts: Sparse Autoencoder Feature Structure

The Geometry of Concepts: Sparse Autoencoder Feature Structure

10 October 2024
Yuxiao Li
Eric J. Michaud
David D. Baek
Joshua Engels
Xiaoqing Sun
Max Tegmark
ArXivPDFHTML

Papers citing "The Geometry of Concepts: Sparse Autoencoder Feature Structure"

6 / 6 papers shown
Title
Empirical Evaluation of Progressive Coding for Sparse Autoencoders
Empirical Evaluation of Progressive Coding for Sparse Autoencoders
Hans Peter
Anders Søgaard
36
0
0
30 Apr 2025
Representation Learning on a Random Lattice
Representation Learning on a Random Lattice
Aryeh Brill
OOD
FAtt
AI4CE
68
0
0
28 Apr 2025
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni
Joshua Engels
Senthooran Rajamanoharan
Max Tegmark
Neel Nanda
56
3
0
23 Feb 2025
Harmonic Loss Trains Interpretable AI Models
Harmonic Loss Trains Interpretable AI Models
David D. Baek
Ziming Liu
Riya Tyagi
Max Tegmark
81
2
0
03 Feb 2025
Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
Rethinking Evaluation of Sparse Autoencoders through the Representation of Polysemous Words
Gouki Minegishi
Hiroki Furuta
Yusuke Iwasawa
Y. Matsuo
49
1
0
09 Jan 2025
Attention Heads of Large Language Models: A Survey
Attention Heads of Large Language Models: A Survey
Zifan Zheng
Yezhaohui Wang
Yuxin Huang
Shichao Song
Mingchuan Yang
Bo Tang
Feiyu Xiong
Zhiyu Li
LRM
41
1
0
05 Sep 2024
1