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Digital Humanities and Cultural Heritage Publications IN

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382 research outcomes, page 1 of 39
  • publication . Preprint . Article . 2021
    Open Access English
    Authors:
    Venugopal, Vineeth; Sahoo, Sourav; Zaki, Mohd; Agarwal, Manish; Gosvami, Nitya Nand; Krishnan, N. M. Anoop;
    Persistent Identifiers

    Highlights • Natural language processing is used for information extraction from research papers • Caption cluster plots are used for exploring figure captions across the entire corpus • Elemental maps are used to identify the chemical elements reported in a study • A f...

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  • publication . Conference object . Preprint . 2021
    Open Access
    Authors:
    Sayar Ghosh Roy; Nikhil Pinnaparaju; Risubh Jain; Manish Gupta; Vasudeva Varma;
    Persistent Identifiers
    Publisher: Association for Computational Linguistics

    Automatic text summarization has been widely studied as an important task in natural language processing. Traditionally, various feature engineering and machine learning based systems have been proposed for extractive as well as abstractive text summarization. Recently,...

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  • publication . Preprint . Conference object . 2020
    Open Access English
    Authors:
    Vaibhav Kumar; Tenzin Bhotia; Vaibhav Kumar;
    Persistent Identifiers

    Comment: 6 pages, 3 figures

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  • publication . Preprint . Conference object . 2020
    Open Access English
    Authors:
    Haozhe Ji; Pei Ke; Shaohan Huang; Furu Wei; Xiaoyan Zhu; Minlie Huang;
    Persistent Identifiers

    Despite the success of generative pre-trained language models on a series of text generation tasks, they still suffer in cases where reasoning over underlying commonsense knowledge is required during generation. Existing approaches that integrate commonsense knowledge i...

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  • publication . Conference object . Preprint . 2020
    Open Access
    Authors:
    Jianqiao Li; Chunyuan Li; Guoyin Wang; Hao Fu; Yuh-Chen Lin; Liqun Chen; Yizhe Zhang; Chenyang Tao; Ruiyi Zhang; Wenlin Wang; ...
    Persistent Identifiers
    Publisher: Association for Computational Linguistics

    Neural language models are often trained with maximum likelihood estimation (MLE), where the next word is generated conditioned on the ground-truth word tokens. During testing, however, the model is instead conditioned on previously generated tokens, resulting in what i...

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  • publication . Conference object . Preprint . 2020
    Open Access
    Authors:
    Saurabh Gupta; Huy H. Nguyen; Junichi Yamagishi; Isao Echizen;
    Persistent Identifiers
    Publisher: Association for Computational Linguistics

    Comment: 11 pages, 4 figures, 6 tables, Accepted at NLP+CSS Workshop at EMNLP 2020

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  • publication . Preprint . Conference object . 2020
    Open Access English
    Authors:
    Wanjun Zhong; Duyu Tang; Zenan Xu; Ruize Wang; Nan Duan; Ming Zhou; Jiahai Wang; Jian Yin;
    Persistent Identifiers

    Comment: EMNLP2020;10 pages

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  • publication . Conference object . Preprint . 2020
    Open Access
    Authors:
    Tao Shen; Yi Mao; Pengcheng He; Guodong Long; Adam Trischler; Weizhu Chen;
    Persistent Identifiers
    Publisher: Association for Computational Linguistics

    In this work, we aim at equipping pre-trained language models with structured knowledge. We present two self-supervised tasks learning over raw text with the guidance from knowledge graphs. Building upon entity-level masked language models, our first contribution is an ...

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  • publication . Preprint . Article . 2020
    Open Access English
    Authors:
    Vinu E. Venugopal; P. Sreenivasa Kumar;
    Persistent Identifiers

    Semantics based knowledge representations such as ontologies are found to be very useful in automatically generating meaningful factual questions. Determining the difficulty level of these system generated questions is helpful to effectively utilize them in various educ...

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  • publication . Conference object . Preprint . 2020
    Open Access
    Authors:
    Hemant Yadav; Sreyan Ghosh; Yi Yu; Rajiv Ratn Shah;
    Persistent Identifiers
    Publisher: ISCA

    Named entity recognition (NER) from text has been a widely studied problem and usually extracts semantic information from text. Until now, NER from speech is mostly studied in a two-step pipeline process that includes first applying an automatic speech recognition (ASR)...

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382 research outcomes, page 1 of 39