Author

Tingzhang Luo

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Preprint Aug 2026

RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs

RoRA is a training-free framework that casts visual token pruning as role-oriented regional evidence allocation, and consistently outperforms strong training-free baselines across LLaVA and Qwen-VL families, retaining most of the unpruned accuracy even at aggressive pruning ratios.

Qiyanhui Lu, Han Wu, Rongjia Xu et al. · 0 citations

Jul 2026

TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding

Trajectory-Aware Commit Gating (TACG), a training-free gate-level decoder that anchors token identities to the base posterior and uses trajectory-aware signals only to decide whether the current proposal is ready to commit, is proposed.

Chengcheng Wang, Tingzhang Luo, Wenhao Li et al. · arXiv.org · 3 citations