S1-Omni: A Unified Multimodal Reasoning Model for Scientific Understanding, Prediction, and Generation
Merged summary
TL;DR - S1-Omni is a unified multimodal model that handles diverse scientific data and tasks within one reasoning framework. It aims to replace fragmented domain-specific systems while achieving strong results across scientific benchmarks.
- Maps text, molecular formats, proteins, spectra, and images into a shared representation space.
- Integrates scientific laws and expert knowledge during data construction and training.
- Supports prediction, molecular generation, protein modeling, and scientific image generation and editing.
- Trained on millions of reasoning samples across 200 tasks and evaluated on more than 60 benchmarks.
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S1-Omni: A Unified Multimodal Reasoning Model for Scientific Understanding, Prediction, and Generation
TL;DR - S1-Omni is a unified multimodal model that handles diverse scientific data and tasks within one reasoning framework. It aims to replace fragmented domain-specific systems while achieving strong results across scientific benchmarks.
- Maps text, molecular formats, proteins, spectra, and images into a shared representation space.
- Integrates scientific laws and expert knowledge during data construction and training.
- Supports prediction, molecular generation, protein modeling, and scientific image generation and editing.
- Trained on millions of reasoning samples across 200 tasks and evaluated on more than 60 benchmarks.