41 citations · 43 across the 9 of their papers we have counts for
9 papers
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…
Voxtral TTS
Mistral-AI, :, Alexander H. Liu +186
We introduce Voxtral TTS, an expressive multilingual text-to-speech model that generates natural speech from as little as 3 seconds of reference audio. Voxtral TTS adopts a hybrid…
Toward Autonomous UI Exploration: The UIExplorer Benchmark
Andrei Cristian Nica, Akshaya Vishnu Kudlu Shanbhogue, Harshil Shah +4
Autonomous agents must know how to explore user interfaces (UIs) for reliable task solving, yet systematic evaluation of this crucial phase is lacking. We introduce UIExplore-Bench…
Generalized Multiple Intent Conditioned Slot Filling
Harshil Shah, Arthur Wilcke, Marius Cobzarenco +3
Natural language understanding includes the tasks of intent detection (identifying a user's objectives) and slot filling (extracting the entities relevant to those objectives). Pri…
Tackling Hate Speech in Low-resource Languages with Context Experts
Daniel Nkemelu, Harshil Shah, Irfan Essa +1
Given Myanmars historical and socio-political context, hate speech spread on social media has escalated into offline unrest and violence. This paper presents findings from our remo…
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…