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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 ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic Relations ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Baylon, Julia; Han, Rujun; Hsu, I-Hung; Ning, Qiang; Peng, Nanyun; Roth, Dan; Sun, Jiao. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.597/ Abstract: Stories and narratives are composed based on a variety of events. Understanding how these events are semantically related to each other is the essence of reading comprehension. Recent event-centric reading comprehension datasets focus on either event arguments or event temporal commonsense. Although these tasks evaluate machines' ability of narrative understanding, human-like reading comprehension requires the capability to process event-based semantics beyond arguments and temporal commonsense. For example, to understand causality between events, we need to infer motivations or purposes; to understand event hierarchy, we need to parse the composition of events. To facilitate these tasks, we introduce ESTER, a comprehensive machine reading comprehension (MRC) dataset for Event Semantic Relation Reasoning. We study the five most commonly used event semantic relations and formulate them as question answering tasks. Experimental ... Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing; Question-Answering Systems URL: https://underline.io/lecture/37869-ester-a-machine-reading-comprehension-dataset-for-reasoning-about-event-semantic-relations https://dx.doi.org/10.48448/xk0s-v563 BASE Hide details 2 Document-level Entity-based Extraction as Template Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Huang, Kung-Hsiang; Peng, Nanyun. - : Underline Science Inc., 2021 BASE Show details 3 Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Chang, Kai-Wei; Hu, Ziniu. - : Underline Science Inc., 2021 BASE Show details 4 ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Han, Rujun; Peng, Nanyun. - : Underline Science Inc., 2021 BASE Show details 5 Improving Pre-trained Vision-and-Language Embeddings for Phrase Grounding ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dou, Zi-Yi; Peng, Nanyun. - : Underline Science Inc., 2021 BASE Show details 6 Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ahmad, Wasi Uddin; Chang, Kai-Wei. - : Underline Science Inc., 2021 BASE Show details 7 AESOP: Paraphrase Generation with Adaptive Syntactic Control ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Ma, Xuezhe; Peng, Nanyun. - : Underline Science Inc., 2021 BASE Show details

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