Author

Sin-Han Yang

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#machine learning Preprint Oct 2026

A Broader Look at Model Merging: Rethinking Implicit Regularization Induced by Task Arithmetic

Model merging aims to build a multi-task model cheaply by combining the weights of individual task-specific models. To perform well across multiple tasks, most existing merging methods use an additional dataset to find the coefficients for the best linear combination of task-specific weight updates. However, we identif...

Sin-Han Yang, Shih-Cheng Huang, Chieh-Yen Lin et al. · 0 citations

#artificial intelligence Feb 2026

On Calibration of Large Language Models: From Response To Capability

Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on response-level confidence, which estimates the correctness of a single generated output. However, this formulation is misaligned with many practical settings where the central qu...

Sin-Han Yang, Cheng-Kuang Wu, Chengxi Wu et al. · arXiv.org · 9 citations