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Monica N Agrawal

2 accepted papers

2022

Co-training Improves Prompt-based Learning for Large Language Models

ICML 2022spotlight

We demonstrate that co-training (Blum & Mitchell, 1998) can improve the performance of prompt-based learning by using unlabeled data. While prompting has emerged as a promising paradigm for few-shot and zero-shot learning, it is often brittle and requires much larger models compared to the standard…

2022

Leveraging Time Irreversibility with Order-Contrastive Pre-training

AISTATS 2022poster

Label-scarce, high-dimensional domains such as healthcare present a challenge for modern machine learning techniques. To overcome the difficulties posed by a lack of labeled data, we explore an "order-contrastive" method for self-supervised pre-training on longitudinal data. We sample pairs of time…

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