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SAEs Are Good for Steering – If You Select the Right Features
Dana Arad, Aaron Mueller, Yonatan BelinkovProceedings of the 2025 Conference on Empirical Methods in Natural Language ProcessingPublished 2025doi 10.18653/v1/2025.emnlp-main.519Original︎ ↗Archived copy
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after filtering out features with low output scores, we obtain 2-3x improvements when steering with SAEs, making them competitive with supervised methods.
On AxBench, SAE steering underperforms both prompting and difference-in-means representations.
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Record
- Kind
- conference paper
- Authors
- Dana Arad, Aaron Mueller, Yonatan Belinkov
- Publisher
- Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
- Published
- 2025
- DOI
- 10.18653/v1/2025.emnlp-main.519
- Link
- https://arxiv.org/abs/2505.20063
- Archived copy
- https://web.archive.org/web/20260606172332/https://arxiv.org/abs/2505.20063
- Stored text
- 4,746 characters, retrieved Nov 12, 2026 · not yet divided
- Claims extracted
- Not recorded
- Versions
- One known
- Copies
- None recorded
- Corrections
- None recorded
- Facts checked
- Nov 12, 2026
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