We demonstrate how a specialized 25B parameter Mistral model, post-trained on domain-specific data, can outperform Google's Gemini 2.5 Flash by double-digit margins on insurance loss run extraction tasks.
Explore the critical challenge of uncertainty quantification in large language models. Learn about confidence estimation techniques, calibration metrics like ECE and MCE, and practical methods to improve model reliability from logit-based approaches to ensemble methods and post-hoc calibration.
A comprehensive survey of multimodal large language models from 2021 to 2024, covering encoder-only models, encoder-decoder architectures, decoder-only models, and specialized applications for documents and screens.
Welcome to our Journal Club! Here, we discuss papers that we find interesting and relevant to our research interests and use-cases. The papers are selected by the team and are presented by members each week! Additionally, a different team member records notes on what was discussed.