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Found 3 papers, 3 papers with code
MotionCLIP: Exposing Human Motion Generation to CLIP Space
MotionCLIP gains its unique power by aligning its latent space with that of the Contrastive Language-Image Pre-training (CLIP) model.
Evaluating the Evaluation of Diversity in Natural Language Generation
Despite growing interest in natural language generation (NLG) models that produce diverse outputs, there is currently no principled method for evaluating the diversity of an NLG system.
Evaluating Text GANs as Language Models
Generative Adversarial Networks (GANs) are a promising approach for text generation that, unlike traditional language models (LM), does not suffer from the problem of ``exposure bias''.
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