FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization

3 November 2023

Papers citing "FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization"

5 / 5 papers shown

Title
Pruning as a Domain-specific LLM Extractor Nan Zhang Yanchi Liu Xujiang Zhao Wei Cheng Runxue Bao Rui Zhang Prasenjit Mitra Haifeng Chen 26 9 0 10 May 2024
Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations Lucy Lu Wang Yulia Otmakhova Jay DeYoung Thinh Hung Truong Bailey Kuehl Erin Bransom Byron C. Wallace 113 20 0 23 May 2023
Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations Longxiang Zhang Renato M. P. Negrinho Arindam Ghosh V. Jagannathan H. Hassanzadeh Thomas Schaaf Matthew R. Gormley LM&MA AI4MH 82 67 0 24 Sep 2021
The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey Yi-Chong Huang Xiachong Feng Xiaocheng Feng Bing Qin HILM 136 105 0 30 Apr 2021
Towards Clinical Encounter Summarization: Learning to Compose Discharge Summaries from Prior Notes Han-Chin Shing Chaitanya P. Shivade Nima Pourdamghani Feng Nan Philip Resnik Douglas W. Oard Parminder Bhatia 60 24 0 27 Apr 2021