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20172026
most citedFew-shot Named Entity Recognition with Entity-level Prototypical Network Enhanced by Dispersedly Distributed Prototypes

16 citations · 36 across the 27 of their papers we have counts for

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Showing 2022 · cs.CLShow all

6 papers · 2 filters

cs.CL2022

Span-based joint entity and relation extraction augmented with sequence tagging mechanism

Bin Ji, Shasha Li, Hao Xu +4

Span-based joint extraction simultaneously conducts named entity recognition (NER) and relation extraction (RE) in text span form. However, since previous span-based models rely on…

cs.CL2022

A Two-Phase Paradigm for Joint Entity-Relation Extraction

Bin Ji, Hao Xu, Jie Yu +4

An exhaustive study has been conducted to investigate span-based models for the joint entity and relation extraction task. However, these models sample a large number of negative e…

cs.CL2022★ 1 cited

A Context-Aware Approach for Textual Adversarial Attack through Probability Difference Guided Beam Search

Huijun Liu, Jie Yu, Shasha Li +2

Textual adversarial attacks expose the vulnerabilities of text classifiers and can be used to improve their robustness. Existing context-aware methods solely consider the gold labe…

cs.CL2022★ 16 cited

Few-shot Named Entity Recognition with Entity-level Prototypical Network Enhanced by Dispersedly Distributed Prototypes

Bin Ji, Shasha Li, Shaoduo Gan +3

Few-shot named entity recognition (NER) enables us to build a NER system for a new domain using very few labeled examples. However, existing prototypical networks for this task suf…

cs.CL2022★ 1 cited

Win-Win Cooperation: Bundling Sequence and Span Models for Named Entity Recognition

Bin Ji, Shasha Li, Jie Yu +2

For Named Entity Recognition (NER), sequence labeling-based and span-based paradigms are quite different. Previous research has demonstrated that the two paradigms have clear compl…

cs.CL2022

SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encoder

Wuhang Lin, Shasha Li, Chen Zhang +4

Text summarization models are often trained to produce summaries that meet human quality requirements. However, the existing evaluation metrics for summary text are only rough prox…