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README.md
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<div align=center><img src="https://raw.githubusercontent.com/tongjingqi/Code2Logic/refs/heads/main/assets/evaluation_results_on_general_vision_benchmarks.png"></div>
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It's also found that getting trained on 5k samples from our GameQA dataset can lead to better results than on [multimodal-open-r1-8k-verified](https://huggingface.co/datasets/lmms-lab/multimodal-open-r1-8k-verified).
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<div align=center><img src="https://raw.githubusercontent.com/tongjingqi/Code2Logic/refs/heads/main/assets/GameQA_generalizes_better.png"></div>
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<div align=center><img src="https://raw.githubusercontent.com/tongjingqi/Code2Logic/refs/heads/main/assets/evaluation_results_on_general_vision_benchmarks.png"></div>
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***(The inference and evaluation configurations were unified across both the original open-source models and our trained models.)***
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It's also found that getting trained on 5k samples from our GameQA dataset can lead to better results than on [multimodal-open-r1-8k-verified](https://huggingface.co/datasets/lmms-lab/multimodal-open-r1-8k-verified).
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<div align=center><img src="https://raw.githubusercontent.com/tongjingqi/Code2Logic/refs/heads/main/assets/GameQA_generalizes_better.png"></div>
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