activity
20222026
most citedModelling graph dynamics in fraud detection with "Attention"

5 citations · 10 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2026

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…

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★ 1 cited

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:…

cs.SE2025★ 2 cited

Devstral: Fine-tuning Language Models for Coding Agent Applications

Abhinav Rastogi, Adam Yang, Albert Q. Jiang +100

We introduce Devstral-Small, a lightweight open source model for code agents with the best performance among models below 100B size. In this technical report, we give an overview o…

cs.SD2025

Voxtral

Alexander H. Liu, Andy Ehrenberg, Andy Lo +103

We present Voxtral Mini and Voxtral Small, two multimodal audio chat models. Voxtral is trained to comprehend both spoken audio and text documents, achieving state-of-the-art perfo…

cs.CL2025★ 2 cited

Magistral

Mistral-AI, :, Abhinav Rastogi +98

We introduce Magistral, Mistral's first reasoning model and our own scalable reinforcement learning (RL) pipeline. Instead of relying on existing implementations and RL traces dist…

cs.CL2025

Distill-C: Enhanced NL2SQL via Distilled Customization with LLMs

Cong Duy Vu Hoang, Gioacchino Tangari, Clemence Lanfranchi +10

The growing adoption of large language models (LLMs) in business applications has amplified interest in Natural Language to SQL (NL2SQL) solutions, in which there is competing dema…

cs.LG2022★ 5 cited

Modelling graph dynamics in fraud detection with "Attention"

Susie Xi Rao, Clémence Lanfranchi, Shuai Zhang +7

At online retail platforms, detecting fraudulent accounts and transactions is crucial to improve customer experience, minimize loss, and avoid unauthorized transactions. Despite th…