metadata
license: apache-2.0
base_model:
- Qwen/Qwen2.5-VL-7B-Instruct
VL-Cogito
The homepage of our multimodal reasoning model—VL-Cogito! Inspired by the Latin word “Cogito” (“I think”), VL-Cogito is built for complex and diverse multimodal reasoning tasks, with a strong focus on autonomous thinking and adaptability.
What makes VL-Cogito stand out?
Progressive Curriculum Reinforcement Learning (PCuRL):Through a multi-stage, “from easy to hard” reinforcement learning approach, VL-Cogito’s reasoning abilities are significantly enhanced across a wide range of multimodal scenarios!
Two key innovations:
- Online difficulty weighting: Dynamically adjusts training difficulty, allowing the model to progress step by step from easier to more challenging examples.
- Dynamic length reward: Encourages the model to adapt the length of its reasoning process based on the complexity of each individual problem, balancing both accuracy and efficiency.
Outstanding Performance:
VL-Cogito demonstrates stable, state-of-the-art or superior results on mainstream multimodal reasoning benchmarks, covering mathematics, science, logic, and commonsense understanding!
