Papers by Jasmine Wang
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation (2021.naacl-demos)
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Qingyun Wang, Manling Li, Xuan Wang, Nikolaus Parulian, Guangxing Han, Jiawei Ma, Jingxuan Tu, Ying Lin, Ranran Haoran Zhang, Weili Liu, Aabhas Chauhan, Yingjun Guan, Bangzheng Li, Ruisong Li, Xiangchen Song, Yi Fung, Heng Ji, Jiawei Han, Shih-Fu Chang, James Pustejovsky, Jasmine Rah, David Liem, Ahmed ELsayed, Martha Palmer, Clare Voss, Cynthia Schneider, Boyan Onyshkevych
| Challenge: | a new framework to digest relevant biomedical knowledge is needed to combat COVID-19 . quantity of research results is a bottleneck, and false information promoted in publications . |
| Approach: | a team of researchers has developed a framework to extract multimedia knowledge elements from scientific literature to combat COVID-19. |
| Outcome: | a new framework extracts fine-grained multimedia knowledge elements from scientific literature . it provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence . the framework is based on a case study of drug repurposing . |
Learning an Unreferenced Metric for Online Dialogue Evaluation (2020.acl-main)
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| Challenge: | Existing tools for dialogue evaluation do not generalize to unseen datasets and/or need a human-generated reference response during inference. |
| Approach: | They propose an unreferenced automated dialogue evaluation metric that uses large pre-trained language models to extract latent representations of utterances and leverages the temporal transitions that exist between them. |
| Outcome: | The proposed model achieves higher correlation with human annotations in an online setting, while not requiring true responses for comparison during inference. |