most citedHuman-like Summarization Evaluation with ChatGPT

38 citations · 40 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023

A New Benchmark and Reverse Validation Method for Passage-level Hallucination Detection

Shiping Yang, Renliang Sun, Xiaojun Wan

Large Language Models (LLMs) have shown their ability to collaborate effectively with humans in real-world scenarios. However, LLMs are apt to generate hallucinations, i.e., makeup…

cs.CL2023

A New Dataset and Empirical Study for Sentence Simplification in Chinese

Shiping Yang, Renliang Sun, Xiaojun Wan

Sentence Simplification is a valuable technique that can benefit language learners and children a lot. However, current research focuses more on English sentence simplification. Th…

cs.CL20232 cited

Teaching the Pre-trained Model to Generate Simple Texts for Text Simplification

Renliang Sun, Wei Xu, Xiaojun Wan

Randomly masking text spans in ordinary texts in the pre-training stage hardly allows models to acquire the ability to generate simple texts. It can hurt the performance of pre-tra…

cs.CL202338 cited

Human-like Summarization Evaluation with ChatGPT

Mingqi Gao, Jie Ruan, Renliang Sun +3

Evaluating text summarization is a challenging problem, and existing evaluation metrics are far from satisfactory. In this study, we explored ChatGPT's ability to perform human-lik…

cs.CL2023

Exploiting Summarization Data to Help Text Simplification

Renliang Sun, Zhixian Yang, Xiaojun Wan

One of the major problems with text simplification is the lack of high-quality data. The sources of simplification datasets are limited to Wikipedia and Newsela, restricting furthe…