Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajectory satisfies the success criteria implied by the user instruction. Existing GUI reward verifiers, however, often under-specify how these criteria should be constructed...
Tao Xiong, Xavier Hu, Wen-Kai Wang et al.· 1 citation
We introduce Xiaomi-TabLDM, a tabular large data foundation model for classification and regression via in-context learning, which delivers superior prediction accuracy without requiring task-specific fine-tuning. Pretrained exclusively on synthetic data generated from structural causal models (SCMs), our model enables...
Xiaomi-TabLDM Team Penghui Wang, Wei Liu, Hong Wang et al.· 0 citations
gui-PRA is introduced, a Process Reward Agent that transforms GUI process evaluation from passive scoring into active investigation, and demonstrates strong competitiveness against fully trained critic models.
Tao Xiong, Xavier Hu, Yurun Chen et al.· arXiv.org· 5 citations
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