TIGER-Lab/PixelReasoner-SFT-Data

Overview. The SFT data for training Pixel Reasoner: Incentivizing Pixel-Space Reasoning with Curiosity-Driven Reinforcement Learning, The queries require fine-grained visual analysis in both images (e.g., infographics, visually-rich scenes, etc) and videos. Details. The data contains 8,000+ reasoning trajectories, including : 2,000+ textual reasoning trajectories, rejection sampled from the base model Qwen2.5-VL-Instruct. These data aims to preserve textual reasoning ability on easier VL… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/PixelReasoner-SFT-

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