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05/25/2023
Passive learning of active causal strategies in agents and language models
What can be learned about causality and experimentation from passive dat...
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05/22/2023
Meta-in-context learning in large language models
Large language models have shown tremendous performance in a variety of ...
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04/12/2023
Meta-Learned Models of Cognition
Meta-learning is a framework for learning learning algorithms through re...
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04/08/2022
Semantic Exploration from Language Abstractions and Pretrained Representations
Continuous first-person 3D environments pose unique exploration challeng...
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04/05/2022
Can language models learn from explanations in context?
Large language models can perform new tasks by adapting to a few in-cont...
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12/07/2021
Tell me why! – Explanations support learning of relational and causal structure
Explanations play a considerable role in human learning, especially in a...
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02/04/2021
Alchemy: A structured task distribution for meta-reinforcement learning
There has been rapidly growing interest in meta-learning as a method for...
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11/26/2020
Meta-learning in natural and artificial intelligence
Meta-learning, or learning to learn, has gained renewed interest in rece...
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08/21/2020
Amortized learning of neural causal representations
Causal models can compactly and efficiently encode the data-generating p...
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07/07/2020
Deep Reinforcement Learning and its Neuroscientific Implications
The emergence of powerful artificial intelligence is defining new resear...
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05/08/2019
Meta-learning of Sequential Strategies
In this report we review memory-based meta-learning as a tool for buildi...
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11/14/2018
Evolving intrinsic motivations for altruistic behavior
Multi-agent cooperation is an important feature of the natural world. Ma...
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05/24/2018
Been There, Done That: Meta-Learning with Episodic Recall
Meta-learning agents excel at rapidly learning new tasks from open-ended...
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11/17/2016
Learning to reinforcement learn
In recent years deep reinforcement learning (RL) systems have attained s...
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02/03/2014