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  # Unified-Reward-7B-v1.5
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  We are actively gathering feedback from the community to improve our models. **We welcome your input and encourage you to stay updated through our repository**!!
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  [2025/4/16] πŸ”₯πŸ”₯ We updated the `UnifiedReward-7B-v1.5` by introducing pointwise scoring for generated images across three dimensions: alignment, coherence, and style, each rated on a continuous scale from 1 to 5.
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  1. **Alignment** quantifies how well an image matches its prompt.
 
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  # Unified-Reward-7B-v1.5
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  We are actively gathering feedback from the community to improve our models. **We welcome your input and encourage you to stay updated through our repository**!!
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+ [2025/10/23] πŸ”₯πŸ”₯πŸ”₯ We release **UnifiedReward-Edit**-[[3b](https://huggingface.co/CodeGoat24/UnifiedReward-Edit-qwen-3b)/[7b](https://huggingface.co/CodeGoat24/UnifiedReward-Edit-qwen-7b)/[32b](https://huggingface.co/CodeGoat24/UnifiedReward-Edit-qwen-32b)], a unified reward model for **both Text-to-Image and Image-to-Image generation** trained on approximately 700K unified image generation and editing reward data!!
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+ For image editing reward task, our models support:
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+ >1. Pairwise Rank β€” directly judge which of two edited images is better.
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+ >2. Pairwise Score β€” assign a separate score to each image in a pair.
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+ >3. Pointwise Score β€” rate a single image on two axes: instruction-following and overall image quality.
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+ πŸš€ The image editing reward inference code is available at [`UnifiedReward-Edit/`](https://github.com/CodeGoat24/UnifiedReward/tree/main/UnifiedReward-Edit) directory, while T2I inference code is unchanged from previous models. The editing training data is preprocessed from [EditScore](https://huggingface.co/datasets/EditScore/EditScore-Reward-Data) and [EditReward](https://huggingface.co/datasets/TIGER-Lab/EditReward-Data) and will be released soon. We sincerely appreciate all contributors!!
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+ [2025/9/25] πŸ”₯πŸ”₯πŸ”₯ We release **UnifiedReward-2.0**-qwen-[[3b](https://huggingface.co/CodeGoat24/UnifiedReward-2.0-qwen-3b)/[7b](https://huggingface.co/CodeGoat24/UnifiedReward-2.0-qwen-7b)/[32b](https://huggingface.co/CodeGoat24/UnifiedReward-2.0-qwen-32b)/[72b](https://huggingface.co/CodeGoat24/UnifiedReward-2.0-qwen-72b)].
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+ This version introduces several new capabilities:
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+ >
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+ >1. **Pairwise scoring** for image and video generation assessment on **_Alignment_**, **_Coherence_**, **_Style_** dimensions.
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+ >2. **Pointwise scoring** for image and video generation assessment on **_Alignment_**, **_Coherence/Physics_**, **_Style_** dimensions.
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+ The added inference code is available at [`inference_qwen/UnifiedReward-2.0-inference`](https://github.com/CodeGoat24/UnifiedReward/tree/main/inference_qwen/UnifiedReward-2.0-inference) directory. The newly added training data has been released [here](https://huggingface.co/datasets/CodeGoat24/UnifiedReward-2.0-T2X-score-data) 😊.
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  [2025/4/16] πŸ”₯πŸ”₯ We updated the `UnifiedReward-7B-v1.5` by introducing pointwise scoring for generated images across three dimensions: alignment, coherence, and style, each rated on a continuous scale from 1 to 5.
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  1. **Alignment** quantifies how well an image matches its prompt.