A process reward model (PRM) for web agents, built by LoRA SFT on Qwen3.5-4B and merged into full weights. It evaluates candidate next actions of web agents at intermediate steps, given the task intent, the current page's accessibility tree (AXTree), and the previous action trajectory. Trained on the surfPRM-data dataset: 9,821 pairwise step-preference samples for web agents. Each sample contains the task intent, the current page's accessibility tree (AXTree), the previous action trajectory, the start/current URLs, and two candidate next actions grounded on the current page; the model outputs structured / / / reasoning and selects the better action. Requires transformers >= 5.6. Load as a…
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PoloWitty
polowitty
Models in Library2
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Models on Hugging Face8
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