no code implementations • 17 Dec 2023 • Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Qingyang Wu, Zhongfen Deng, Jiangshu Du, Shuaiqi Liu, Yunlong Xu, Philip S. Yu
Task-Oriented Parsing (TOP) enables conversational assistants to interpret user commands expressed in natural language, transforming them into structured outputs that combine elements of both natural language and intent/slot tags.
no code implementations • 7 Nov 2023 • Zhongfen Deng, Seunghyun Yoon, Trung Bui, Franck Dernoncourt, Quan Hung Tran, Shuaiqi Liu, Wenting Zhao, Tao Zhang, Yibo Wang, Philip S. Yu
Then we merge the sentences selected for a specific aspect as the input for the summarizer to produce the aspect-based summary.
1 code implementation • 7 Nov 2023 • Zhongfen Deng, Hao Peng, Tao Zhang, Shuaiqi Liu, Wenting Zhao, Yibo Wang, Philip S. Yu
Furthermore, the copy mechanism in value generator and the value attention module in value classifier help our model address the data discrepancy issue by only focusing on the relevant part of input text and ignoring other information which causes the discrepancy issue such as sentence structure in the text.
1 code implementation • 11 Oct 2023 • Zhongfen Deng, Wei-Te Chen, Lei Chen, Philip S. Yu
In this paper, we reformulate this task as a multi-label classification task that can be applied for real-world scenario in which only annotation of attribute values is available to train models (i. e., annotation of positional information of attribute values is not available).
no code implementations • 20 Sep 2023 • Wenting Zhao, Ye Liu, Yao Wan, Yibo Wang, Zhongfen Deng, Philip S. Yu
Furthermore, TAG-QA outperforms the end-to-end model T5 by 16% and 12% on BLEU-4 and PARENT F-score, respectively.
1 code implementation • 20 Sep 2023 • Yibo Wang, Wenting Zhao, Yao Wan, Zhongfen Deng, Philip S. Yu
In this paper, we propose to incorporate the label dependencies among entity types into a multi-task learning framework for better MRC-based NER.
no code implementations • 28 Oct 2022 • Byung-Hak Kim, Zhongfen Deng, Philip S. Yu, Varun Ganapathi
The medical codes prediction problem from clinical notes has received substantial interest in the NLP community, and several recent studies have shown the state-of-the-art (SOTA) code prediction results of full-fledged deep learning-based methods.
1 code implementation • NAACL 2021 • Zhongfen Deng, Hao Peng, Dongxiao He, JianXin Li, Philip S. Yu
The second one encourages the structure encoder to learn better representations with desired characteristics for all labels which can better handle label imbalance in hierarchical text classification.
1 code implementation • COLING 2020 • Zhongfen Deng, Hao Peng, Congying Xia, JianXin Li, Lifang He, Philip S. Yu
Review rating prediction of text reviews is a rapidly growing technology with a wide range of applications in natural language processing.