most citedSurvival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 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.CL2026

Phoenix-VL 1.5 Medium Technical Report

Team Phoenix, :, Arka Ray +29

We introduce Phoenix-VL 1.5 Medium, a 123B-parameter natively multimodal and multilingual foundation model, adapted to regional languages and the Singapore context. Developed as a…

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★ 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:…

stat.ML2024★ 2 cited

Survival Models: Proper Scoring Rule and Stochastic Optimization with Competing Risks

Julie Alberge, Vincent Maladière, Olivier Grisel +2

When dealing with right-censored data, where some outcomes are missing due to a limited observation period, survival analysis -- known as time-to-event analysis -- focuses on predi…

cs.AI2024

Teaching Models To Survive: Proper Scoring Rule and Stochastic Optimization with Competing Risks

Julie Alberge, Vincent Maladière, Olivier Grisel +2

When data are right-censored, i.e. some outcomes are missing due to a limited period of observation, survival analysis can compute the "time to event". Multiple classes of outcomes…