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1
What is Your Article Based On? Inferring Fine-grained Provenance ...
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{Z}ero-shot {L}abel-Aware {E}vent {T}rigger and {A}rgument {C}lassification ...
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3
Coreference Reasoning in Machine Reading Comprehension ...
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4
Event-Centric Natural Language Processing ...
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5
Zero-shot Event Extraction via Transfer Learning: Challenges and Insights ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-short.42 Abstract: Event extraction has long been a challenging task, addressed mostly with supervised methods that require expensive annotation and are not extensible to new event ontologies. In this work, we explore the possibility of zero-shot event extraction by formulating it as a set of Textual Entailment (TE) and/or Question Answering (QA) queries (e.g. "A city was attacked" entails "There is an attack"), exploiting pretrained TE/QA models for direct transfer. On ACE-2005 and ERE, our system achieves acceptable results, yet there is still a large gap from supervised approaches, showing that current QA and TE technologies fail in transferring to a different domain. To investigate the reasons behind the gap, we analyze the remaining key challenges, their respective impact, and possible improvement directions. ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/3snf-wq75
https://underline.io/lecture/25455-zero-shot-event-extraction-via-transfer-learning-challenges-and-insights
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6
Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary ...
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7
Constrained Labeled Data Generation for Low-Resource Named Entity Recognition ...
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