Papers by Ryan Moreno

2 papers
RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models (2021.emnlp-main)

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Challenge: Recent named entity recognition models have great performance on many conventional benchmarks, but it is not reliable in realistic applications.
Approach: They propose a method to create natural adversarial examples using Wikidata and pre-trained language models.
Outcome: The proposed method produces natural adversarial examples with a shifted distribution from training data.
TriggerNER: Learning with Entity Triggers as Explanations for Named Entity Recognition (2020.acl-main)

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Challenge: Named entity recognition (NER) is a fundamental information extraction task that focuses on extracting entities from a given text and classifying them using pre-defined categories.
Approach: They propose to use “entity triggers” to facilitate label-efficient learning of NER models.
Outcome: The proposed model is significantly more cost-effective than the traditional neural NER frameworks.

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