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06/28/2023
Towards Measuring the Representation of Subjective Global Opinions in Language Models
Large language models (LLMs) may not equitably represent diverse global ...
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04/15/2023
Learned Interpolation for Better Streaming Quantile Approximation with Worst-Case Guarantees
An ε-approximate quantile sketch over a stream of n inputs approximates ...
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02/15/2023
The Capacity for Moral Self-Correction in Large Language Models
We test the hypothesis that language models trained with reinforcement l...
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12/15/2022
Constitutional AI: Harmlessness from AI Feedback
As AI systems become more capable, we would like to enlist their help to...
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11/16/2022
Engineering Monosemanticity in Toy Models
In some neural networks, individual neurons correspond to natural “featu...
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11/06/2022
Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks
Recent work shows that the expressive power of Graph Neural Networks (GN...
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11/04/2022
Measuring Progress on Scalable Oversight for Large Language Models
Developing safe and useful general-purpose AI systems will require us to...
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09/21/2022
Toy Models of Superposition
Neural networks often pack many unrelated concepts into a single neuron ...
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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...
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07/11/2022
Language Models (Mostly) Know What They Know
We study whether language models can evaluate the validity of their own ...
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01/14/2019
