作者位次 #6/7ICLR 2026Poster· Social Aspects / Trustworthy Machine Learning
MUSE: Model-Agnostic Tabular Watermarking via Multi-Sample Selection
Liancheng Fang · Aiwei Liu · Henry Peng Zou · Yankai Chen · Hengrui Zhang · Zhongfen Deng · Philip Yu
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Liancheng Fang · Aiwei Liu · Henry Peng Zou · Yankai Chen · Hengrui Zhang · Zhongfen Deng · Philip Yu
Yibo Wang · Congying Xia · Wenting Zhao · Jiangshu Du · Chunyu Miao · Zhongfen Deng · Philip S. Yu · Chen Xing
Unit test generation has become a promising and important use case for Large Language Models (LLMs). However, existing evaluation benchmarks for LLM unit test generation primarily focus on function- or class-level code (single-file) rather than on more practical, challenging multi-file codebases....