A theory of incremental compression. - Arthur Franz; Oleksandr Antonenko; Roman Soletskyi (Inf. Sci., 2021)

Training Safe Neural Networks with Global SDP Bounds. - Roman Soletskyi; David Dalrymple (CoRR, 2024)

Pixtral 12B. - Pravesh Agrawal; Szymon Antoniak; Emma Bou Hanna; Baptiste Bout; Devendra Singh Chaplot; Jessica Chudnovsky; Diogo Costa; Baudouin De Monicault; Saurabh Garg; Théophile Gervet; Soham Ghosh; Amélie Héliou; et al. (CoRR, 2024)

A theoretical perspective on mode collapse in variational inference. - Roman Soletskyi; Marylou Gabrié; Bruno Loureiro (CoRR, 2024)

CombiBench: Benchmarking LLM Capability for Combinatorial Mathematics. - Junqi Liu; Xiaohan Lin; Jonas Bayer; Yael Dillies; Weijie Jiang; Xiaodan Liang; Roman Soletskyi; Haiming Wang; Yunzhou Xie; Beibei Xiong; Zhengfeng Yang; Jujian Zhang; et al. (CoRR, 2025)

Magistral. - Abhinav Rastogi; Albert Q. Jiang; Andy Lo; Gabrielle Berrada; Guillaume Lample; Jason Rute; Joep Barmentlo; Karmesh Yadav; Kartik Khandelwal; Khyathi Raghavi Chandu; Léonard Blier; Lucile Saulnier; et al. (CoRR, 2025)

Voxtral. - Alexander H. Liu; Andy Ehrenberg; Andy Lo; Clément Denoix; Corentin Barreau; Guillaume Lample; Jean-Malo Delignon; Khyathi Raghavi Chandu; Patrick von Platen; Pavankumar Reddy Muddireddy; Sanchit Gandhi; Soham Ghosh; et al. (CoRR, 2025)