FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Datasets Dependency

Seonglae Cho, Harryn Oh, Donghyun Lee, Luis Rodrigues Vieira, Andrew Bermingham, Ziad El Sayed. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop). 2025.

Authors

Z. Sayed (ORCID: https://orcid.org/0009-0009-1019-2775)
Lina Vieira (ORCID: https://orcid.org/0000-0002-7109-6535)
Hyun-Joo Oh
Dong‐Hyun Lee (ORCID: https://orcid.org/0000-0001-7588-4769)
Seonglae Cho
A Bermingham

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.18653/v1/2025.acl-srw.20
Primary Topic: Generative Adversarial Networks and Image Synthesis
Type: article
Field-Weighted Citation Impact: 0.00

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article

FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Datasets Dependency

Z. Sayed, Lina Vieira, Hyun-Joo Oh, Dong‐Hyun Lee et al.

Jan 1, 2025

Generative Adversarial Networks and Image Synthesis

article

FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Datasets Dependency

Z. Sayed, Lina Vieira, Hyun-Joo Oh, Dong‐Hyun Lee, Seonglae Cho, A Bermingham

January 1, 2025article en

Abstract

Openalex Percentile: Top 83%

Generative Adversarial Networks and Image Synthesis

DOI Open Access PDF OpenAlex

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FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Datasets Dependency — Z. Sayed, Lina Vieira, et al. · (2025) | TGRS Research Map | TGRS