1 citations · 2 across the 8 of their papers we have counts for
8 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…
Voxtral Realtime
Mistral-AI, :, Alexander H. Liu +166
We introduce Voxtral Realtime, a natively streaming automatic speech recognition model that matches offline transcription quality at sub-second latency. Unlike approaches that adap…
Ministral 3
Alexander H. Liu, Kartik Khandelwal, Sandeep Subramanian +116
We introduce the Ministral 3 series, a family of parameter-efficient dense language models designed for compute and memory constrained applications, available in three model sizes:…
Towards Zero-Shot Multimodal Machine Translation
Matthieu Futeral, Cordelia Schmid, Benoît Sagot +1
Current multimodal machine translation (MMT) systems rely on fully supervised data (i.e models are trained on sentences with their translations and accompanying images). However, t…
mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus
Matthieu Futeral, Armel Zebaze, Pedro Ortiz Suarez +5
Multimodal Large Language Models (mLLMs) are trained on a large amount of text-image data. While most mLLMs are trained on caption-like data only, Alayrac et al. (2022) showed that…
MAD Speech: Measures of Acoustic Diversity of Speech
Matthieu Futeral, Andrea Agostinelli, Marco Tagliasacchi +2
Generative spoken language models produce speech in a wide range of voices, prosody, and recording conditions, seemingly approaching the diversity of natural speech. However, the e…
Tackling Ambiguity with Images: Improved Multimodal Machine Translation and Contrastive Evaluation
Matthieu Futeral, Cordelia Schmid, Ivan Laptev +2
One of the major challenges of machine translation (MT) is ambiguity, which can in some cases be resolved by accompanying context such as images. However, recent work in multimodal…