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20162022
most citedNamed Entity Recognition as Dependency Parsing

19 citations · 30 across the 3 of their papers we have counts for

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8 papers · 1 filter

cs.CL20223 cited

Coreference Resolution through a seq2seq Transition-Based System

Bernd Bohnet, Chris Alberti, Michael Collins

Most recent coreference resolution systems use search algorithms over possible spans to identify mentions and resolve coreference. We instead present a coreference resolution syste…

cs.CL202019 cited

Named Entity Recognition as Dependency Parsing

Juntao Yu, Bernd Bohnet, Massimo Poesio

Named Entity Recognition (NER) is a fundamental task in Natural Language Processing, concerned with identifying spans of text expressing references to entities. NER research is oft…

cs.CL2020

On Faithfulness and Factuality in Abstractive Summarization

Joshua Maynez, Shashi Narayan, Bernd Bohnet +1

It is well known that the standard likelihood training and approximate decoding objectives in neural text generation models lead to less human-like responses for open-ended tasks s…

cs.CL2019

Neural Mention Detection

Juntao Yu, Bernd Bohnet, Massimo Poesio

Mention detection is an important preprocessing step for annotation and interpretation in applications such as NER and coreference resolution, but few stand-alone neural models hav…

cs.CL2018

82 Treebanks, 34 Models: Universal Dependency Parsing with Multi-Treebank Models

Aaron Smith, Bernd Bohnet, Miryam de Lhoneux +3

We present the Uppsala system for the CoNLL 2018 Shared Task on universal dependency parsing. Our system is a pipeline consisting of three components: the first performs joint word…

cs.CL2018

Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings

Bernd Bohnet, Ryan McDonald, Goncalo Simoes +3

The rise of neural networks, and particularly recurrent neural networks, has produced significant advances in part-of-speech tagging accuracy. One characteristic common among these…