4 papers
Multiple-Choice Questions are Efficient and Robust LLM Evaluators
Ziyin Zhang, Zhaokun Jiang, Lizhen Xu +2
We present GSM-MC, a multiple-choice (MC) dataset constructed by collecting answers and incorrect predictions on GSM8K from 60 open-source models. Through extensive experiments, we…
Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models
Zhiwei He, Binglin Zhou, Hongkun Hao +5
Text watermarking technology aims to tag and identify content produced by large language models (LLMs) to prevent misuse. In this study, we introduce the concept of cross-lingual c…
Improving Open-Ended Text Generation via Adaptive Decoding
Wenhong Zhu, Hongkun Hao, Zhiwei He +2
Current language models decode text token by token according to probabilistic distribution, and determining the appropriate candidates for the next token is crucial to ensure gener…
CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models
Wenhong Zhu, Hongkun Hao, Zhiwei He +6
We are currently in an era of fierce competition among various large language models (LLMs) continuously pushing the boundaries of benchmark performance. However, genuinely assessi…