Open multimodal reasoning models have benefited from large-scale reasoning supervision, yet reliable post-training remains challenging due to uneven data quality, inefficient supervision construction, imbalanced difficulty, and cross-domain interference. We introduce MMVistaReason (MVR), an open-data post-training reci...
Jue-Kai Lin, Hong-Lin Lin, Yu-Qian Yuan et al.· 0 citations
SPARK (Scientific Paper Abstracted Reasoning sKeleton), a paper-oriented synthesis framework built on Sci-Base, is introduced, a scientific reasoning dataset with substantially higher difficulty and diversity than existing resources and consistently outperforms existing scientific reasoning datasets.
A novel Dual Self-Consistency Reinforcement Learning optimization paradigm is introduced, which utilizes Round-Trip Verification to penalize degenerate code and boost overall self-consistency in TikZ code.
Juekai Lin, Yun Zhu, Honglin Lin et al.· arXiv.org· 5 citations
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