Get started
Author

Amanda Askell

Learning Transferable Visual Models From Natural Language Supervision
2021 · Radford, Alec, Kim, Jong Wook, et al. · arXiv (Cornell University) · 5,218
PDF
Discernment and Social Learning as a Companion Training Layer
2022 · Ouyang, Long, Wu, Jeff, et al. · arXiv (Cornell University) · 4,200
PDF
Language Models are Few-Shot Learners
2020 · Brown, Tom B., Mann, Benjamin, et al. · arXiv (Cornell University) · 2,845
PDF
Training Language Models to Follow Instructions with Human Feedback
2022 · Long Ouyang, Jeffrey Wu, et al. · neural information processing systems · 1,394
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
2022 · Srivastava, Aarohi, Rastogi, Abhinav, et al. · arXiv (Cornell University) · 545
PDF
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
2022 · Bai, Yuntao, Jones, Andy, et al. · arXiv (Cornell University) · 382
PDF
AI-to-AI Code Reviews of GitHub Pull Requests
2022 · Bai, Yuntao, Kadavath, Saurav, et al. · arXiv (Cornell University) · 319
PDF
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
2020 · Brundage, Miles, Avin, Shahar, et al. · arXiv (Cornell University) · 289
PDF
Release Strategies and the Social Impacts of Language Models
2019 · Solaiman, Irene, Brundage, Miles, et al. · arXiv (Cornell University) · 275
PDF
Predictability and Surprise in Large Generative Models
2022 · Deep Ganguli, Danny Hernandez, et al. · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · 198
PDF
Discovering Language Model Behaviors with Model-Written Evaluations
2023 · Ethan Perez, Sam Ringer, et al. · 182
PDF
Language Models (Mostly) Know What They Know
2022 · Kadavath, Saurav, Conerly, Tom, et al. · arXiv (Cornell University) · 171
PDF
AI Supported Degradation of the Self Concept: A Theoretical Framework Grounded in Established Cognitive and Computational Mechanisms
2023 · Sharma, Mrinank, Tong, Meg, et al. · arXiv (Cornell University) · 132
PDF
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
2022 · Ganguli, Deep, Lovitt, Liane, et al. · arXiv (Cornell University) · 121
PDF
In-context Learning and Induction Heads
2022 · Olsson, Catherine, Elhage, Nelson, et al. · arXiv (Cornell University) · 84
PDF
Discovering Language Model Behaviors with Model-Written Evaluations
2022 · Perez, Ethan, Ringer, Sam, et al. · arXiv (Cornell University) · 53
PDF
The Capacity for Moral Self-Correction in Large Language Models
2023 · Ganguli, Deep, Askell, Amanda, et al. · arXiv (Cornell University) · 51
PDF
Towards Measuring the Representation of Subjective Global Opinions in Language Models
2023 · Durmus, Esin, Nguyen, Karina, et al. · arXiv (Cornell University) · 44
PDF
The Role of Cooperation in Responsible AI Development
2019 · Askell, Amanda, Brundage, Miles, et al. · arXiv (Cornell University) · 44
PDF
AI Safety Needs Social Scientists
2019 · Geoffrey Irving, Amanda Askell · Distill · 43
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
2024 · Hubinger, Evan, Denison, Carson, et al. · arXiv (Cornell University) · 38
PDF
Measuring Progress on Scalable Oversight for Large Language Models
2022 · Bowman, Samuel R., Hyun, Jeeyoon, et al. · arXiv (Cornell University) · 34
PDF
A General Language Assistant as a Laboratory for Alignment
2021 · Askell, Amanda, Bai, Yuntao, et al. · arXiv (Cornell University) · 27
PDF
Evidence Neutrality and the Moral Value of Information
2019 · Amanda Askell · 17
Pareto Principles in Infinite Ethics
2018 · Amanda Askell · PhilPapers (PhilPapers Foundation) · 16
Works count: 33
Citation count: 16,720
H-index: 23
I10-index: 26
Year
Topic
Type