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Found 3 papers, 2 papers with code
Gradient-based Planning with World Models
The enduring challenge in the field of artificial intelligence has been the control of systems to achieve desired behaviours.
End-to-End Speech Recognition and Disfluency Removal with Acoustic Language Model Pretraining
In light of recent successes in large scale audio pretraining, we revisit the performance comparison between two-stage and end-to-end model and find that audio based language models pretrained using weak self-supervised objectives match or exceed the performance of similarly trained two-stage models, and further, that the choice of pretraining objective substantially effects a model's ability to be adapted to the disfluency removal task.
Joint Embedding Predictive Architectures Focus on Slow Features
Many common methods for learning a world model for pixel-based environments use generative architectures trained with pixel-level reconstruction objectives.
