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Found 2 papers, 2 papers with code
Hybrid Inverse Reinforcement Learning
In this work, we propose using hybrid RL -- training on a mixture of online and expert data -- to curtail unnecessary exploration.
Test-Time Distribution Normalization for Contrastively Learned Vision-language Models
Advances in the field of vision-language contrastive learning have made it possible for many downstream applications to be carried out efficiently and accurately by simply taking the dot product between image and text representations.
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