Haiying Deng — accepted AI-conference papers

2024

NewsBench: A Systematic Evaluation Framework for Assessing Editorial Capabilities of Large Language Models in Chinese Journalism

Miao Li, Ming-Bin Chen, Bo Tang, ShengbinHou ShengbinHou, Pengyu Wang, Haiying Deng +5

ACL 2024long

We present NewsBench, a novel evaluation framework to systematically assess the capabilities of Large Language Models (LLMs) for editorial capabilities in Chinese journalism. Our constructed benchmark dataset is focused on four facets of writing proficiency and six facets of safety adherence, and it…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗

2024

UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation

Xun Liang, Shichao Song, Simin Niu, Zhiyu Li, Feiyu Xiong, Bo Tang +5

ACL 2024long

Large language models (LLMs) produce hallucinated text, compromising their practical utility in professional contexts. To assess the reliability of LLMs, numerous initiatives have developed benchmark evaluations for hallucination phenomena. However, they often employ constrained generation technique…

Cited by 30 Source ↗PDF ↗code ↗Scholar ↗