Joseph, Nicholas
Anthropic (United States)
4 papers on CoChat
Most cited papers
- Verified
Evaluating Large Language Models Trained on Code
Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. D. O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., et al. (2021) · arXiv
Software Engineering ResearchNatural Language Processing Techniques
Cited by 1,436
- Verified
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
- Verified
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
- Verified
A General Language Assistant as a Laboratory for Alignment
Askell, A., Bai, Y., Chen, A., Drain, D., Ganguli, D., Henighan, T., Jones, A., Joseph, N., Mann, B., DasSarma, N., et al. (2021) · arXiv
Topic ModelingEthics and Social Impacts of AI
Cited by 146
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