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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 – 7 of 7 1 FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bansal, Mohit; Guo, Han. - : Underline Science Inc., 2021 BASE Show details 2 ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bansal, Mohit; Bauer, Lisa. - : Underline Science Inc., 2021 BASE Show details 3 Inducing Transformer’s Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bansal, Mohit; Jiang, Yichen. - : Underline Science Inc., 2021 BASE Show details 4 Integrating Visuospatial, Linguistic, and Commonsense Structure into Story Visualization ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bansal, Mohit; Maharana, Adyasha. - : Underline Science Inc., 2021 BASE Show details 5 Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Ramakanth; Bansal, Mohit; Dagan, Ido; Ernst, Ori; Goldberger, Jacob; Lepioshkin, Michael; Shapira, Ori. - : Underline Science Inc., 2021 Abstract: Aligning sentences in a reference summary with their counterparts in source documents was shown as a useful auxiliary summarization task, notably for generating training data for salience detection. Despite its assessed utility, the alignment step was mostly approached with heuristic unsupervised methods, typically ROUGE-based, and was never independently optimized or evaluated. In this paper, we propose establishing summary-source alignment as an explicit task, while introducing two major novelties: (1) applying it at the more accurate proposition span level, and (2) approaching it as a supervised classification task. To that end, we created a novel training dataset for proposition-level alignment, derived automatically from available summarization evaluation data. In addition, we crowdsourced dev and test datasets, enabling model development and proper evaluation. Utilizing these data, we present a supervised proposition alignment baseline model, showing improved alignment-quality over the unsupervised ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Text Summarization URL: https://underline.io/lecture/39850-summary-source-proposition-level-alignment-task,-datasets-and-supervised-baseline https://dx.doi.org/10.48448/jb9p-zd26 BASE Hide details 6 Continual Few-Shot Learning for Text Classification ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Ramakanth; Bansal, Mohit. - : Underline Science Inc., 2021 BASE Show details 7 Finding a Balanced Degree of Automation for Summary Evaluation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bansal, Mohit; Zhang, Shiyue. - : Underline Science Inc., 2021 BASE Show details

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