16 citations · 18 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
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…
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…
Topic-Grained Text Representation-based Model for Document Retrieval
Mengxue Du, Shasha Li, Jie Yu +5
Document retrieval enables users to find their required documents accurately and quickly. To satisfy the requirement of retrieval efficiency, prevalent deep neural methods adopt a…