Reference Matters: Benchmarking Factual Error Correction for Dialogue
Summarization with Fine-grained Evaluation Framework

Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework

8 June 2023

Xiaojun Wan

Papers citing "Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework"

5 / 5 papers shown

Title
Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart Captioning Kung-Hsiang Huang Mingyang Zhou Hou Pong Chan Yi R. Fung Zhenhailong Wang Lingyu Zhang Shih-Fu Chang Chenhui Xu 21 33 0 15 Dec 2023
Improving Factual Consistency in Summarization with Compression-Based Post-Editing Alexander R. Fabbri Prafulla Kumar Choubey Jesse Vig Chien-Sheng Wu Caiming Xiong HILM KELM 46 17 0 11 Nov 2022
Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling Vidhisha Balachandran Hannaneh Hajishirzi William W. Cohen Yulia Tsvetkov HILM KELM 92 46 0 22 Oct 2022
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics Artidoro Pagnoni Vidhisha Balachandran Yulia Tsvetkov HILM 233 306 0 27 Apr 2021
Factual Error Correction for Abstractive Summarization Models Mengyao Cao Yue Dong Jiapeng Wu Jackie C.K. Cheung HILM KELM 169 159 0 17 Oct 2020