Image-Text-to-Text
Transformers
Safetensors
qwen3
text-generation
conversational
text-generation-inference
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@@ -10,10 +10,6 @@ WebGen-Agent is an advanced website generation agent designed to autonomously cr
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  WebGen-Agent combines state-of-the-art language models with specialized training techniques to create a powerful website generation tool. The agent can understand natural language instructions specifying appearance and functional requirements, iteratively generate website codebases, and refine them using visual and functional feedback.
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- ![WebGen-Agent Workflow](fig/webgen-agent.png)
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- ![Step-GRPO with Screenshot and GUI-agent Feedback](fig/step-grpo.png)
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  ## Resources
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  Links to the data and model parameters are as follows:
@@ -42,12 +38,7 @@ WebGen-Agent follows an iterative, multi-step paradigm for website generation:
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  - A GUI-agent tests the website functionality and provides functional feedback
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  4. **Refinement**: Based on the feedback, the agent continues to improve the website until it meets requirements
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- ## Key Features
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- - **Iterative Refinement**: Continuously improves website appearance and functionality
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- - **Feedback Integration**: Uses both visual and functional feedback for enhanced performance
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- - **Backtracking Mechanism**: Reverts to previous states when encountering persistent errors
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- - **Best Step Selection**: Selects the optimal version based on screenshot and GUI-agent scores
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  ## Step-GRPO with Screenshot and GUI-agent Feedback
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@@ -57,6 +48,8 @@ The Step-GRPO with Screenshot and GUI-agent Feedback approach uses the screensho
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  These dual rewards provide dense, reliable process supervision that significantly improves the model's ability to generate high-quality websites.
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  ## Citation
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  If you find our project useful, please cite:
 
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  WebGen-Agent combines state-of-the-art language models with specialized training techniques to create a powerful website generation tool. The agent can understand natural language instructions specifying appearance and functional requirements, iteratively generate website codebases, and refine them using visual and functional feedback.
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  ## Resources
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  Links to the data and model parameters are as follows:
 
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  - A GUI-agent tests the website functionality and provides functional feedback
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  4. **Refinement**: Based on the feedback, the agent continues to improve the website until it meets requirements
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+ ![WebGen-Agent Workflow](fig/webgen-agent.png)
 
 
 
 
 
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  ## Step-GRPO with Screenshot and GUI-agent Feedback
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  These dual rewards provide dense, reliable process supervision that significantly improves the model's ability to generate high-quality websites.
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+ ![Step-GRPO with Screenshot and GUI-agent Feedback](fig/step-grpo.png)
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+
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  ## Citation
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  If you find our project useful, please cite: