Conerly, Tom

In-context Learning and Induction Heads

Olsson, C., Elhage, N., Nanda, N., Joseph, N., DasSarma, N., Henighan, T., Mann, B., Askell, A., Bai, Y., Chen, A., et al. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 1,170

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Bai, Y., Jones, A., Ndousse, K., Askell, A., Chen, A., DasSarma, N., Drain, D., Fort, S., Ganguli, D., Henighan, T., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 442

Predictability and Surprise in Large Generative Models

Ganguli, D., Hernandez, D., Lovitt, L., DasSarma, N., Henighan, T., Jones, A., Joseph, N., Kernion, J., Mann, B., Askell, A., et al. (2022) · arXiv

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 324

Predictability and Surprise in Large Generative Models

Ganguli, D., Hernandez, D., Lovitt, L., Askell, A., Bai, Y., Chen, A., Conerly, T., Dassarma, N., Drain, D., Elhage, N., et al. (2022) · 2022 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 207

Language Models (Mostly) Know What They Know

Kadavath, S., Conerly, T., Askell, A., Henighan, T., Drain, D., Perez, E., Schiefer, N., Hatfield-Dodds, Z., DasSarma, N., Tran-Johnson, E., et al. (2022) · arXiv

Topic ModelingAdversarial Robustness in Machine Learning

Cited by 187

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

Ganguli, D., Lovitt, L., Kernion, J., Askell, A., Bai, Y., Kadavath, S., Mann, B., Perez, E., Schiefer, N., Ndousse, K., et al. (2022) · arXiv

Adversarial Robustness in Machine LearningEthics and Social Impacts of AI

Cited by 130

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

Scaling Laws and Interpretability of Learning from Repeated Data

Hernandez, D., Brown, T., Conerly, T., DasSarma, N., Drain, D., El-Showk, S., Elhage, N., Hatfield-Dodds, Z., Henighan, T., Hume, T., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 24