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Found 5 papers, 1 papers with code
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models
When LLMs perform zero-shot inference, they typically use a prompt with a task specification, and generate a completion.
BatchPrompt: Accomplish more with less
We have two initial observations for prompting with batched data.
Discovering Distribution Shifts using Latent Space Representations
Rapid progress in representation learning has led to a proliferation of embedding models, and to associated challenges of model selection and practical application.
Importance Weighted Generative Networks
Deep generative networks can simulate from a complex target distribution, by minimizing a loss with respect to samples from that distribution.
Directing Generative Networks with Weighted Maximum Mean Discrepancy
In this paper, we construct an estimator for the MMD between P and Q when we only have access to P via some biased sample selection mechanism, and suggest methods for estimating this sample selection mechanism when it is not already known.
