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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Yuanzhi; Hasan, Mohammad. - : Underline Science Inc., 2021 BASE Show details 2 Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Zuo, Simiao. - : Underline Science Inc., 2021 BASE Show details 3 An Investigation into the Contribution of Locally Aggregated Descriptors to Figurative Language Identification ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Indrakshi; Banerjee, Ritwik. - : Underline Science Inc., 2021 BASE Show details 4 Context-Aware Interaction Network for Question Matching ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Hu, Zhe. - : Underline Science Inc., 2021 BASE Show details 5 SciBERT-based Multitasking Deep Neural Architecture to identify Contribution Statements from Scientific articles ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Tirthankar; Ahmad, Ammaar; Ekbal, Asif; Gupta, Komal. - : Underline Science Inc., 2021 Abstract: The exponential growth in the scientific literature in recent years has to lead to a serious scholarly information overload on researchers. Automatically identifying the specific contribution made in a research paper would help quicker comprehension of the work, faster literature survey, comparison with the related works, etc. Here in this work, we propose a method to automatically extract the contribution statements from research articles. We design a model (ContriSci) multi-task deep neural network leveraging section identification and citance classification of scientific statements to predict whether a given scientific sentence specifies a contribution or not. Our long-term goal, we create a knowledge graph of scientific contributions for machine comprehension and more straightforward navigation of research contributions for a particular domain. Our proposed model achieves the best performance over earlier methods (a relative improvement of 8.08% in terms ofF1score) for contributing sentence ... Keyword: Computational Linguistics; Deep Learning; Language Models; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Neural Network URL: https://dx.doi.org/10.48448/3xnm-nw44 https://underline.io/lecture/39682-scibert-based-multitasking-deep-neural-architecture-to-identify-contribution-statements-from-scientific-articles BASE Hide details 6 Certified Robustness to Programmable Transformations in LSTMs ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Zhang, Yuhao. - : Underline Science Inc., 2021 BASE Show details 7 DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep Learning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Guo, Quan; Kordjamshidi, Parisa. - : Underline Science Inc., 2021 BASE Show details 8 Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chen, Yangyi. - : Underline Science Inc., 2021 BASE Show details 9 Powering Comparative Classification with Sentiment Analysis via Domain Adaptive Knowledge Transfer ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Li, Zeyu. - : Underline Science Inc., 2021 BASE Show details

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