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01/31/2023
Scaling laws for single-agent reinforcement learning
Recent work has shown that, in generative modeling, cross-entropy loss i...
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10/19/2022
Scaling Laws for Reward Model Overoptimization
In reinforcement learning from human feedback, it is common to optimize ...
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05/28/2022
Teaching Models to Express Their Uncertainty in Words
We show that a GPT-3 model can learn to express uncertainty about its ow...
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03/04/2022
Training language models to follow instructions with human feedback
Making language models bigger does not inherently make them better at fo...
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12/17/2021
WebGPT: Browser-assisted question-answering with human feedback
We fine-tune GPT-3 to answer long-form questions using a text-based web-...
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10/27/2021
Training Verifiers to Solve Math Word Problems
State-of-the-art language models can match human performance on many tas...
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10/01/2021
Batch size-invariance for policy optimization
We say an algorithm is batch size-invariant if changes to the batch size...
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09/08/2021
TruthfulQA: Measuring How Models Mimic Human Falsehoods
We propose a benchmark to measure whether a language model is truthful i...
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03/29/2021
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark
The NeurIPS 2020 Procgen Competition was designed as a centralized bench...
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09/09/2020
Phasic Policy Gradient
We introduce Phasic Policy Gradient (PPG), a reinforcement learning fram...
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12/03/2019
