Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Deng, Zhongfen"'
Autor:
Du, Jiangshu, Wang, Yibo, Zhao, Wenting, Deng, Zhongfen, Liu, Shuaiqi, Lou, Renze, Zou, Henry Peng, Venkit, Pranav Narayanan, Zhang, Nan, Srinath, Mukund, Zhang, Haoran Ranran, Gupta, Vipul, Li, Yinghui, Li, Tao, Wang, Fei, Liu, Qin, Liu, Tianlin, Gao, Pengzhi, Xia, Congying, Xing, Chen, Cheng, Jiayang, Wang, Zhaowei, Su, Ying, Shah, Raj Sanjay, Guo, Ruohao, Gu, Jing, Li, Haoran, Wei, Kangda, Wang, Zihao, Cheng, Lu, Ranathunga, Surangika, Fang, Meng, Fu, Jie, Liu, Fei, Huang, Ruihong, Blanco, Eduardo, Cao, Yixin, Zhang, Rui, Yu, Philip S., Yin, Wenpeng
This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and question answering, significantly reducing the time required for many rout
Externí odkaz:
http://arxiv.org/abs/2406.16253
Autor:
Zhao, Wenting, Liu, Ye, Wan, Yao, Wang, Yibo, Wu, Qingyang, Deng, Zhongfen, Du, Jiangshu, Liu, Shuaiqi, Xu, Yunlong, Yu, Philip S.
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. Recently, Large Lan
Externí odkaz:
http://arxiv.org/abs/2312.10771
Autor:
Deng, Zhongfen, Yoon, Seunghyun, Bui, Trung, Dernoncourt, Franck, Tran, Quan Hung, Liu, Shuaiqi, Zhao, Wenting, Zhang, Tao, Wang, Yibo, Yu, Philip S.
Aspect-based meeting transcript summarization aims to produce multiple summaries, each focusing on one aspect of content in a meeting transcript. It is challenging as sentences related to different aspects can mingle together, and those relevant to a
Externí odkaz:
http://arxiv.org/abs/2311.04292
Autor:
Deng, Zhongfen, Peng, Hao, Zhang, Tao, Liu, Shuaiqi, Zhao, Wenting, Wang, Yibo, Yu, Philip S.
Product attribute value extraction is an important task in e-Commerce which can help several downstream applications such as product search and recommendation. Most previous models handle this task using sequence labeling or question answering method
Externí odkaz:
http://arxiv.org/abs/2311.04196
Publikováno v:
2022 IEEE International Conference on Big Data, pages 1816-1821
Product attribute value extraction plays an important role for many real-world applications in e-Commerce such as product search and recommendation. Previous methods treat it as a sequence labeling task that needs more annotation for position of valu
Externí odkaz:
http://arxiv.org/abs/2310.07137
Question answering on tabular data (a.k.a TableQA), which aims at generating answers to questions grounded on a provided table, has gained significant attention recently. Prior work primarily produces concise factual responses through information ext
Externí odkaz:
http://arxiv.org/abs/2309.11049
Named Entity Recognition (NER) aims to extract and classify entity mentions in the text into pre-defined types (e.g., organization or person name). Recently, many works have been proposed to shape the NER as a machine reading comprehension problem (a
Externí odkaz:
http://arxiv.org/abs/2309.11027
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. Ho
Externí odkaz:
http://arxiv.org/abs/2210.15882
The current state-of-the-art model HiAGM for hierarchical text classification has two limitations. First, it correlates each text sample with all labels in the dataset which contains irrelevant information. Second, it does not consider any statistica
Externí odkaz:
http://arxiv.org/abs/2104.05220
Review rating prediction of text reviews is a rapidly growing technology with a wide range of applications in natural language processing. However, most existing methods either use hand-crafted features or learn features using deep learning with simp
Externí odkaz:
http://arxiv.org/abs/2011.00802