38 citations · 99 across the 23 of their papers we have counts for
8 papers · 1 filter
Image Matters: A New Dataset and Empirical Study for Multimodal Hyperbole Detection
Huixuan Zhang, Xiaojun Wan
Hyperbole, or exaggeration, is a common linguistic phenomenon. The detection of hyperbole is an important part of understanding human expression. There have been several studies on…
Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework
Mingqi Gao, Xiaojun Wan, Jia Su +2
Factuality is important to dialogue summarization. Factual error correction (FEC) of model-generated summaries is one way to improve factuality. Current FEC evaluation that relies…
SituatedGen: Incorporating Geographical and Temporal Contexts into Generative Commonsense Reasoning
Yunxiang Zhang, Xiaojun Wan
Recently, commonsense reasoning in text generation has attracted much attention. Generative commonsense reasoning is the task that requires machines, given a group of keywords, to…
Is Summary Useful or Not? An Extrinsic Human Evaluation of Text Summaries on Downstream Tasks
Xiao Pu, Mingqi Gao, Xiaojun Wan
Research on automated text summarization relies heavily on human and automatic evaluation. While recent work on human evaluation mainly adopted intrinsic evaluation methods, judgin…
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…
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…
Models See Hallucinations: Evaluating the Factuality in Video Captioning
Hui Liu, Xiaojun Wan
Video captioning aims to describe events in a video with natural language. In recent years, many works have focused on improving captioning models' performance. However, like other…
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…