research
∙
06/28/2023
Towards Measuring the Representation of Subjective Global Opinions in Language Models
Large language models (LLMs) may not equitably represent diverse global ...
share
research
∙
02/15/2023
The Capacity for Moral Self-Correction in Large Language Models
We test the hypothesis that language models trained with reinforcement l...
research
∙
12/15/2022
Constitutional AI: Harmlessness from AI Feedback
As AI systems become more capable, we would like to enlist their help to...
research
∙
09/24/2022
In-context Learning and Induction Heads
"Induction heads" are attention heads that implement a simple algorithm ...
research
∙
08/23/2022
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
We describe our early efforts to red team language models in order to si...
research
∙
07/11/2022
Language Models (Mostly) Know What They Know
We study whether language models can evaluate the validity of their own ...
research
∙
05/21/2022
Scaling Laws and Interpretability of Learning from Repeated Data
Recent large language models have been trained on vast datasets, but als...
research
∙
04/12/2022
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
We apply preference modeling and reinforcement learning from human feedb...
research
∙
02/15/2022
Predictability and Surprise in Large Generative Models
Large-scale pre-training has recently emerged as a technique for creatin...
research
∙
12/01/2021
A General Language Assistant as a Laboratory for Alignment
Given the broad capabilities of large language models, it should be poss...
research
∙
02/02/2021
Scaling Laws for Transfer
We study empirical scaling laws for transfer learning between distributi...
research
∙
05/08/2020