most citedDevstral: Fine-tuning Language Models for Coding Agent Applications

2 citations · 4 across the 3 of their papers we have counts for

collaborators

6 papers

cs.SE20252 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.IR2025

Aligned Query Expansion: Efficient Query Expansion for Information Retrieval through LLM Alignment

Adam Yang, Gustavo Penha, Enrico Palumbo +1

With the breakthroughs in large language models (LLMs), query generation techniques that expand documents and queries with related terms are becoming increasingly popular in the in…

cs.CL20252 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.CV2025

Reconstructing Tornadoes in 3D with Gaussian Splatting

Adam Yang, Nadula Kadawedduwa, Tianfu Wang +9

Accurately reconstructing the 3D structure of tornadoes is critically important for understanding and preparing for this highly destructive weather phenomenon. While modern 3D scen…

cs.LG2024

Super Resolution On Global Weather Forecasts

Lawrence Zhang, Adam Yang, Rodz Andrie Amor +2

Weather forecasting is a vitally important tool for tasks ranging from planning day to day activities to disaster response planning. However, modeling weather has proven to be chal…