Author

Jun Ling

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Preprint Aug 2026

Teaching MLLMs to Say No: Generalized Referring Expression Comprehension via Refusal Calibrated GRPO

Refusal-Calibrated Group Relative Policy Optimization (RC-GRPO) is proposed, a calibrated RL strategy that strengthens the refusal ability of MLLMs while preserving localization performance, and enforces"None" outputs in rollouts for valid advantage estimation on negative samples and applies a penalty to prevent over-refusal on positives, achieving a balanced trade-off between accuracy and reliability.

Xuzheng Yang, Jun Ling, Tao Huang et al. · 1 citation

Jul 2026

GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models

This work proposes Greedy Orthogonal Token Selection (GOTS), a training-free and query-agnostic method that achieves higher average performance retention than the strongest evaluated baselines, and a controlled OCRBench study shows that it reduces model-side time-to-first-token after accounting for selection overhead.

Jun Ling, Tao Huang, Junzhuo Liu et al. · arXiv.org · 0 citations