1 citations · 1 across the 7 of their papers we have counts for
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Shieldstral
Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +273
We introduce Shieldstral, a 3B-parameter policy-adaptive multimodal safety classifier that matches or outperforms models nearly 7 its size on text safety benchmarks and set…
Locally-Contextual Nonlinear CRFs for Sequence Labeling
Harshil Shah, Tim Xiao, David Barber
Linear chain conditional random fields (CRFs) combined with contextual word embeddings have achieved state of the art performance on sequence labeling tasks. In many of these tasks…
Learning Informative Representations of Biomedical Relations with Latent Variable Models
Harshil Shah, Julien Fauqueur
Extracting biomedical relations from large corpora of scientific documents is a challenging natural language processing task. Existing approaches usually focus on identifying a rel…
Generating Sentences Using a Dynamic Canvas
Harshil Shah, Bowen Zheng, David Barber
We introduce the Attentive Unsupervised Text (W)riter (AUTR), which is a word level generative model for natural language. It uses a recurrent neural network with a dynamic attenti…
Generative Neural Machine Translation
Harshil Shah, David Barber
We introduce Generative Neural Machine Translation (GNMT), a latent variable architecture which is designed to model the semantics of the source and target sentences. We modify an…