ISQA: Informative Factuality Feedback for Scientific Summarization

20 April 2024

Papers citing "ISQA: Informative Factuality Feedback for Scientific Summarization"

7 / 7 papers shown

Title
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation Sewon Min Kalpesh Krishna Xinxi Lyu M. Lewis Wen-tau Yih Pang Wei Koh Mohit Iyyer Luke Zettlemoyer Hannaneh Hajishirzi HILM ALM 113 683 0 23 May 2023
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing Zhibin Gou Zhihong Shao Yeyun Gong Yelong Shen Yujiu Yang Nan Duan Weizhu Chen KELM LRM 61 382 0 19 May 2023
Large Language Models Can Self-Improve Jiaxin Huang S. Gu Le Hou Yuexin Wu Xuezhi Wang Hongkun Yu Jiawei Han ReLM AI4MH LRM 149 608 0 20 Oct 2022
Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization Pengcheng He Baolin Peng Liyang Lu Song Wang Jie Mei ... Chenguang Zhu Wayne Xiong Michael Zeng Jianfeng Gao Xuedong Huang 54 47 0 21 Aug 2022
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries Alex Jinpeng Wang Kyunghyun Cho M. Lewis HILM 77 480 0 08 Apr 2020
Answers Unite! Unsupervised Metrics for Reinforced Summarization Models Thomas Scialom Sylvain Lamprier Benjamin Piwowarski Jacopo Staiano 68 149 0 04 Sep 2019
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering Zhilin Yang Peng Qi Saizheng Zhang Yoshua Bengio William W. Cohen Ruslan Salakhutdinov Christopher D. Manning RALM 150 2,635 0 25 Sep 2018