collaborators

17 papers

cs.CL2026

Shieldstral

Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +274

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…

cs.RO2026

Robostral Navigate

Abhijeet Somani, Arjun Majumdar, Abdelaziz Bounhar +273

Deploying navigation systems at scale requires a recipe that minimizes sensor assumptions, generalizes across robot embodiments, and trains efficiently. Yet, today's best systems d…

cs.AI2026

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…

cs.AI2026

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…

cs.CL2026

Gender Bias in MT for a Genderless Language: New Benchmarks for Basque

Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez

Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…

cs.CL2026

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:…