AI Research
WebGrader: Training LLMs for Web Development with Self-Evolving Programmatic Grader
Automating the evaluation of LLM-generated websites with self-evolving programmatic flow contracts.
Large language models increasingly generate complete websites from natural-language descriptions, and reinforcement learning has become a central approach to closing their remaining functional gap. This training regime is bottlenecked by reward design. Hand-authored browser scrip...
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ArXiv CS.AI
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ArXiv CS.AI
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WebGrader shifts the burden of reinforcement learning from brittle hand-coded scripts to an autonomous system that evolves its own verification logic. By grounding browser interactions in executable flow contracts, it significantly improves functional accuracy for LLMs generating complex web interfaces.
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