Update README.md

README.md

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 - llava-hf/llava-onevision-qwen2-7b-ov-hf
 ---
 
-***This model (GameQA-LLaVA-OV-7b) results from training llava-onevision-qwen2-7b-ov-hf with GRPO solely on our [GameQA](https://huggingface.co/datasets/Gabriel166/GameQA-140K) dataset.***
+***This model (GameQA-InternVL3-8B) results from training InternVL3-8B with GRPO solely on our [GameQA-5K](https://huggingface.co/datasets/Code2Logic/GameQA-5K) (sampled from the full [GameQA-140K](https://huggingface.co/datasets/Gabriel166/GameQA-140K) dataset).***
 
 # Evaluation Results on General Vision BenchMarks
 
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 This is the first work, to the best of our knowledge, that leverages ***game code*** to synthesize multimodal reasoning data for ***training*** VLMs. Furthermore, when trained with a GRPO strategy solely on **GameQA** (synthesized via our proposed **Code2Logic** approach), multiple cutting-edge open-source models exhibit significantly enhanced out-of-domain generalization.
 
-[[📖 Paper](https://arxiv.org/abs/2505.13886)] [🤗 [GameQA-140K Dataset](https://huggingface.co/datasets/Gabriel166/GameQA-140K)] [🤗 [GameQA-InternVL3-8B](https://huggingface.co/Code2Logic/GameQA-InternVL3-8B) ] [🤗 [GameQA-Qwen2.5-VL-7B](https://huggingface.co/Code2Logic/GameQA-Qwen2.5-VL-7B)] [🤗 [GameQA-LLaVA-OV-7B](https://huggingface.co/Code2Logic/GameQA-llava-onevision-qwen2-7b-ov-hf) ]
+[[📖 Paper](https://arxiv.org/abs/2505.13886)] [[🤗 GameQA-140K Dataset](https://huggingface.co/datasets/Gabriel166/GameQA-140K)] [[🤗 GameQA-5K Dataset](https://huggingface.co/datasets/Code2Logic/GameQA-5K)] [[🤗 GameQA-InternVL3-8B](https://huggingface.co/Code2Logic/GameQA-InternVL3-8B) ] [[🤗 GameQA-Qwen2.5-VL-7B](https://huggingface.co/Code2Logic/GameQA-Qwen2.5-VL-7B)] [[🤗 GameQA-LLaVA-OV-7B](https://huggingface.co/Code2Logic/GameQA-llava-onevision-qwen2-7b-ov-hf) ]
 
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