GAS is presented, a generation-guided training framework that reinterprets visual generation as auxiliary supervision for representation learning and improves aggregate multimodal understanding, with its most reliable gains on perception and spatial comprehension.
Zhongbin Guo, Jiahao Xie, Dongling Xiao et al.· 1 citation
The DecoupleMix framework delivers two critical capabilities: guiding what data to collect next and rendering dataset validation a controlled, attributable experiment, and is competitive with strong open-source models trained with substantially larger multimodal budgets.
Jiahao Xie, Zhongbin Guo, Qianle Wang et al.· arXiv.org· 0 citations
This work proposes PRISM, a four-stage data synthesis framework that produces persona--task pairs, prefix-guided rule sets, quality-filtered rubrics, and structured verification traces, and introduces PRISM-Eval, whose Loose and Strict metrics use deterministic matching against fixed labels and therefore require no inf...
Xiaomin He, Dongling Xiao, Jiahao Xie et al.· 0 citations
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