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20192022
most citedHierarchical Entity Typing via Multi-level Learning to Rank

1 citations · 2 across the 6 of their papers we have counts for

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cs.CL2022

An Empirical Study on Finding Spans

Weiwei Gu, Boyuan Zheng, Yunmo Chen +2

We present an empirical study on methods for span finding, the selection of consecutive tokens in text for some downstream tasks. We focus on approaches that can be employed in tra…

cs.CL2022

Asking the Right Questions in Low Resource Template Extraction

Nils Holzenberger, Yunmo Chen, Benjamin Van Durme

Information Extraction (IE) researchers are mapping tasks to Question Answering (QA) in order to leverage existing large QA resources, and thereby improve data efficiency. Especial…

cs.CL2021

Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction

Mahsa Yarmohammadi, Shijie Wu, Marc Marone +10

Zero-shot cross-lingual information extraction (IE) describes the construction of an IE model for some target language, given existing annotations exclusively in some other languag…

cs.CL2021

LOME: Large Ontology Multilingual Extraction

Patrick Xia, Guanghui Qin, Siddharth Vashishtha +7

We present LOME, a system for performing multilingual information extraction. Given a text document as input, our core system identifies spans of textual entity and event mentions…

cs.CL20201 cited

Pattern-aware Data Augmentation for Query Rewriting in Voice Assistant Systems

Yunmo Chen, Sixing Lu, Fan Yang +3

Query rewriting (QR) systems are widely used to reduce the friction caused by errors in a spoken language understanding pipeline. However, the underlying supervised models require…

cs.CL20201 cited

Hierarchical Entity Typing via Multi-level Learning to Rank

Tongfei Chen, Yunmo Chen, Benjamin Van Durme

We propose a novel method for hierarchical entity classification that embraces ontological structure at both training and during prediction. At training, our novel multi-level lear…