activity
20242026
most citedMagistral

2 citations · 6 across the 17 of their papers we have counts for

collaborators

19 papers

cs.CL2026

CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees

S M Rafiuddin, Atriya Sen

Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…

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.RO2026

Robostral Navigate

Abdelaziz Bounhar, Abhijeet Somani, Aditi Kabra +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.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.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.CL2025

From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation

Seokhee Hong, Sunkyoung Kim, Guijin Son +3

The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…

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

Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems

Shang-Chi Tsai, Yun-Nung Chen

With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…

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

Dialect Normalization using Large Language Models and Morphological Rules

Antonios Dimakis, John Pavlopoulos, Antonios Anastasopoulos

Natural language understanding systems struggle with low-resource languages, including many dialects of high-resource ones. Dialect-to-standard normalization attempts to tackle thi…

cs.CL2025

Jailbreak Distillation: Renewable Safety Benchmarking

Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5

Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…

cs.CL2025

ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition

Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2

We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…

cs.CL2025★ 1 cited

Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study

Menglong Cui, Pengzhi Gao, Wei Liu +2

Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…

cs.SE2025

SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Yuxiang Wei, Olivier Duchenne, Jade Copet +6

The recent DeepSeek-R1 release has demonstrated the immense potential of reinforcement learning (RL) in enhancing the general reasoning capabilities of large language models (LLMs)…

cs.CL2024

LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Jan Pfister, Julia Wunderle, Andreas Hotho

We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…

cs.AI2024

The Llama 3 Herd of Models

Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…