DDI-MuG: Multi-aspect graphs for drug-drug interaction extraction

Autor: Jie Yang, Yihao Ding, Siqu Long, Josiah Poon, Soyeon Caren Han

Publikováno v: Frontiers in Digital Health, Vol 5 (2023)

IntroductionDrug-drug interaction (DDI) may lead to adverse reactions in patients, thus it is important to extract such knowledge from biomedical texts. However, previously proposed approaches typically focus on capturing sentence-aspect information

Externí odkaz: https://doaj.org/article/db642ce725aa4cea863769fda7b45851

Tutorials at The Web Conference 2023

Autor: Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espin-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Kücük Mcginty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram Van Den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Ethan Yifan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu

Publikováno v: Companion Proceedings of the ACM Web Conference 2023.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::841d3da4783be7eeee78aa68e7b58e55
https://doi.org/10.1145/3543873.3587713

PiggyBack: Pretrained Visual Question Answering Environment for Backing up Non-deep Learning Professionals

Autor: Zhihao Zhang, Siwen Luo, Junyi Chen, Sijia Lai, Siqu Long, Hyunsuk Chung, Soyeon Caren Han

We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the full stack of visual question answering tasks, specifically data process

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80dc95fbcc1f781efeae81153a3e3f47

Bi-Directional Joint Neural Networks for Intent Classification and Slot Filling

Autor: Soyeon Caren Han, Siqu Long, Josiah Poon, Henry Weld, Huichun Li

Publikováno v: Interspeech 2021.

Intent classification and slot filling are two critical tasks for natural language understanding. Traditionally the two tasks proceeded independently. However, more recently joint models for intent classification and slot filling have achieved state-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81735e899b249d67690454ae7ce729b1
https://doi.org/10.21437/interspeech.2021-2044

CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection

Autor: Guanghao Huang, Jean Lee, Xinghong Guo, Siqu Long, Tongshu Zhang, Josiah Poon, Henry Weld, Kunze Wang, Caren Han

Publikováno v: ACL/IJCNLP (Findings)

Traditional toxicity detection models have focused on the single utterance level without deeper understanding of context. We introduce CONDA, a new dataset for in-game toxic language detection enabling joint intent classification and slot filling ana

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2fdd8c8f9bb4438f15ccf3fa23d7b24
https://doi.org/10.18653/v1/2021.findings-acl.213