LIBERO is a new benchmark for lifelong robot learning that evaluates transfer of declarative, procedural, and mixed knowledge across 130 manipulation tasks with provided demonstration data.
Continual lifelong learning in natural language processing: A survey
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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The relative rankings of continual learning methods are not preserved across different fine-tuning regimes defined by trainable parameter depth.
citing papers explorer
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LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
LIBERO is a new benchmark for lifelong robot learning that evaluates transfer of declarative, procedural, and mixed knowledge across 130 manipulation tasks with provided demonstration data.
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Fine-Tuning Regimes Define Distinct Continual Learning Problems
The relative rankings of continual learning methods are not preserved across different fine-tuning regimes defined by trainable parameter depth.