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05/31/2023
Let's Verify Step by Step
In recent years, large language models have greatly improved in their ab...
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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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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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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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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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12/03/2019
Leveraging Procedural Generation to Benchmark Reinforcement Learning
In this report, we introduce Procgen Benchmark, a suite of 16 procedural...
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03/08/2018
Reptile: a Scalable Metalearning Algorithm
This paper considers metalearning problems, where there is a distributio...
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11/09/2016
RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning
Deep reinforcement learning (deep RL) has been successful in learning so...
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06/21/2016
Concrete Problems in AI Safety
Rapid progress in machine learning and artificial intelligence (AI) has ...
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06/05/2016
