Promptbreeder evolves both task prompts and the mutation prompts that improve them using LLMs, outperforming Chain-of-Thought and Plan-and-Solve on arithmetic and commonsense reasoning benchmarks.
Human-timescale adaptation in an open-ended task space.arXiv preprint arXiv:2301.07608,
3 Pith papers cite this work, alongside 22 external citations. Polarity classification is still indexing.
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A multi-task multi-modal transformer policy pretrained on offline trajectories from thousands of RL environments matches task-specific reference policies on approximately 1000 environments spanning robotics, driving, inventory, cybersecurity, trading, and games.
A survey provides a task-based formalization of meta-learning and meta-RL while chronicling algorithms that lead to DeepMind's Adaptive Agent.
citing papers explorer
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Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution
Promptbreeder evolves both task prompts and the mutation prompts that improve them using LLMs, outperforming Chain-of-Thought and Plan-and-Solve on arithmetic and commonsense reasoning benchmarks.
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Towards Scalable Multi-Task Reinforcement Learning with Large Decision Models
A multi-task multi-modal transformer policy pretrained on offline trajectories from thousands of RL environments matches task-specific reference policies on approximately 1000 environments spanning robotics, driving, inventory, cybersecurity, trading, and games.
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Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agent
A survey provides a task-based formalization of meta-learning and meta-RL while chronicling algorithms that lead to DeepMind's Adaptive Agent.