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Found 3 papers, 2 papers with code
Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent
We present Chirpy Cardinal, an open-domain social chatbot.
MoCo-Pretraining Improves Representations and Transferability of Chest X-ray Models
Using 0. 1% of labeled training data, we find that a linear model trained on MoCo-pretrained representations outperforms one trained on representations without MoCo-pretraining by an AUC of 0. 096 (95% CI 0. 061, 0. 130), indicating that MoCo-pretrained representations are of higher quality.
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
In this work, we propose MoCo-CXR, which is an adaptation of the contrastive learning method Momentum Contrast (MoCo), to produce models with better representations and initializations for the detection of pathologies in chest X-rays.
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