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  # CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
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- πŸ“–<a href="https://huggingface.co/papers/2509.22647">Paper</a> | πŸ’»<a href="https://github.com/InternLM/CapRL">Code</a> | πŸ€—<a href="https://huggingface.co/internlm/CapRL-3B">CapRL-3B Model</a> |
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- πŸ€—<a href="https://huggingface.co/datasets/internlm/CapRL-2M">CapRL-2M Dataset</a> |πŸ€—<a href="https://huggingface.co/collections/long-xing1/caprl-68d64ac32ded31596c36e189">CapRL Collection</a>
 
 
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  **CapRL-Eval-3B** is the model used for answering questions based on captions, and it is a finetuned version of Qwen2.5-VL-3B. When dealing with tasks such as ChartQA (not multiple-choice questions), it provides more stable output formatting.
 
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  # CapRL: Stimulating Dense Image Caption Capabilities via Reinforcement Learning
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+ πŸ“–<a href="https://arxiv.org/abs/2509.22647">Paper</a> | 🏠<a href="https://github.com/InternLM/CapRL">Github</a> |πŸ€—<a href="https://huggingface.co/internlm/CapRL-3B">CapRL-3B Model</a> |πŸ€—<a href="https://huggingface.co/yuhangzang/CapRL-InternVL3.5-8B">CapRL-InternVL3.5-8B Model</a> |
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+ πŸ€—<a href="https://huggingface.co/datasets/internlm/CapRL-2M">CapRL-2M Dataset</a>
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+ πŸ€—<a href="https://huggingface.co/collections/long-xing1/caprl-68d64ac32ded31596c36e189">CapRL Collection</a> | πŸ€—<a href="https://huggingface.co/papers/2509.22647">Daily Paper</a> ο½œπŸ€—<a href="https://huggingface.co/mradermacher/CapRL-3B-GGUF">CapRL-3B-GGUF</a> ο½œπŸ€—<a href="https://huggingface.co/mradermacher/CapRL-3B-i1-GGUF">CapRL-3B-i1-GGUF</a>
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  **CapRL-Eval-3B** is the model used for answering questions based on captions, and it is a finetuned version of Qwen2.5-VL-3B. When dealing with tasks such as ChartQA (not multiple-choice questions), it provides more stable output formatting.