Haoran Ye — LessWrong

LESSWRONG
LW

Training Superior Sparse Autoencoders for Instruct Models

8mo

Resource	Link
Paper	https://arxiv.org/abs/2506.07691
Code	https://github.com/Geaming2002/FAST
SAEs	Llama-3.1-8B-Instruct_SAEs🤗,Llama-3.2-3B-Instruct_SAEs🤗,Llama-3.2-1B-Instruct_SAEs🤗,Qwen2.5-7B-Instruct_SAEs🤗,Qwen2.5-3B-Instruct_SAEs🤗,Qwen2.5-1.5B-Instruct_SAEs🤗,Qwen2.5-0.5B-Instruct_SAEs🤗

💡 TL;DR
In this paper, we discover problems in previous SAE training approaches for instruct model :

📚 Suboptimal dataset selection affecting SAE performance.

✂️ Semantic discontinuity caused by block training truncating samples mid-content.

Therefore, we propose Finetuning-aligned Sequential Training (FAST)💪, a novel training method specifically tailored for instruct models. The results demonstrate:

Token Reconstruction Performance 📉: FAST shows token better reconstruction performance. On Qwen2.5-7B-Instruct, FAST achieves a mean squared error of 0.6468, significantly outperforming baseline methods with errors of 5.1985 and 1.5096.

Feature Interpretability 🎯: FAST yields a higher proportion of high-quality features. For Llama3.2-3B-Instruct, 21.1% scored in the top range, compared to 7.0% and 10.2% for BT(P) and BT(F).

Novel Discovery 🔍: Intervening on the activations of

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