Cunningham, Hoagy

Sparse Autoencoders Find Highly Interpretable Features in Language Models

Cunningham, H., Ewart, A., Riggs, L., Huben, R., & Sharkey, L. (2023) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 61

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet

Templeton, A., Conerly, T., Marcus, J., Lindsey, J., Bricken, T., Chen, B., Pearce, A., Citro, C., Ameisen, E., Jones, A., et al. (2026) · arXiv

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 36

Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming

Sharma, M., Tong, M., Mu, J., Wei, J., Kruthoff, J., Goodfriend, S., Ong, E., Peng, A., Agarwal, R., Anil, C., et al. (2025) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 7

Auditing language models for hidden objectives

Marks, S., Treutlein, J., Bricken, T., Lindsey, J., Marcus, J., Mishra-Sharma, S., Ziegler, D., Ameisen, E., Batson, J., Belonax, T., et al. (2025) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 4