Author

Ruihan Yang

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#machine learning Preprint Sep 2026

Dissecting Training-Free Uncertainty Estimation in Multimodal LLMs

This work presents a systematic study of training-free uncertainty quantification strategies for MLLMs, categorizing existing approaches into three conceptual families: token-level methods, which operate directly in the text output space; ver-balized methods, which elicit uncertainty estimates or abstention signals via...

Soroush Seifi, Vaggelis Dorovatas, Lin Li et al. · 0 citations

#natural language process... Jun 2026

When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs

It is shown that raw global calibration metrics are not robust for cross-model comparison, and that fair calibration comparison requires accuracy-aware evaluation, and proposed ACE, an accuracy-controlled evaluation framework, is proposed.

Zhichao Yang, Caiqi Zhang, Ruihan Yang et al. · arXiv.org · 1 citation