no code implementations • BioNLP (ACL) 2022 • Liyan Tang, Shravan Kooragayalu, Yanshan Wang, Ying Ding, Greg Durrett, Justin F. Rousseau, Yifan Peng
Generating a summary from findings has been recently explored (Zhang et al., 2018, 2020) in note types such as radiology reports that typically have short length.
1 code implementation • 16 Apr 2024 • Liyan Tang, Philippe Laban, Greg Durrett
We release LLM-AggreFact, code for data synthesis, and models.
1 code implementation • 20 Feb 2024 • Liyan Tang, Igor Shalyminov, Amy Wing-mei Wong, Jon Burnsky, Jake W. Vincent, Yu'an Yang, Siffi Singh, Song Feng, Hwanjun Song, Hang Su, Lijia Sun, Yi Zhang, Saab Mansour, Kathleen McKeown
We find that there are diverse errors and error distributions in model-generated summaries and that non-LLM based metrics can capture all error types better than LLM-based evaluators.
no code implementations • 30 May 2023 • Liyan Tang, Yifan Peng, Yanshan Wang, Ying Ding, Greg Durrett, Justin F. Rousseau
To tackle this problem, we propose a controlled text generation method that uses a novel contrastive learning strategy to encourage models to differentiate between generating likely and less likely outputs according to humans.
1 code implementation • 25 May 2022 • Liyan Tang, Tanya Goyal, Alexander R. Fabbri, Philippe Laban, Jiacheng Xu, Semih Yavuz, Wojciech Kryściński, Justin F. Rousseau, Greg Durrett
We compare performance of state-of-the-art factuality metrics, including recent ChatGPT-based metrics, on this stratified benchmark and show that their performance varies significantly across different types of summarization models.
no code implementations • 11 Jan 2022 • Song Wang, Liyan Tang, Mingquan Lin, George Shih, Ying Ding, Yifan Peng
In this work, we propose to mine and represent the associations among medical findings in an informative knowledge graph and incorporate this prior knowledge with radiology report generation to help improve the quality of generated reports.
no code implementations • 28 Oct 2021 • Ajay Jaiswal, Liyan Tang, Meheli Ghosh, Justin Rousseau, Yifan Peng, Ying Ding
Radiology reports are unstructured and contain the imaging findings and corresponding diagnoses transcribed by radiologists which include clinical facts and negated and/or uncertain statements.
no code implementations • 14 Oct 2021 • Liyan Tang, Dhruv Rajan, Suyash Mohan, Abhijeet Pradhan, R. Nick Bryan, Greg Durrett
We show that regularization with small amounts of evidence supervision during training can substantially improve the quality of extracted evidence.
no code implementations • 25 Nov 2020 • Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Song Wang, Ahmed Tewfik, George Shih, Ying Ding, Yifan Peng
After a number of iterations and with the help of radiomic features, our framework can converge to more accurate image regions.