activity
20212023
most citedA Simple but Effective Bidirectional Framework for Relational Triple Extraction

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2023★ 1 cited

Hybrid Retrieval and Multi-stage Text Ranking Solution at TREC 2022 Deep Learning Track

Guangwei Xu, Yangzhao Zhang, Longhui Zhang +3

Large-scale text retrieval technology has been widely used in various practical business scenarios. This paper presents our systems for the TREC 2022 Deep Learning Track. We explai…

cs.CL2022★ 3 cited

A Simple but Effective Bidirectional Framework for Relational Triple Extraction

Feiliang Ren, Longhui Zhang, Xiaofeng Zhao +3

Tagging based relational triple extraction methods are attracting growing research attention recently. However, most of these methods take a unidirectional extraction framework tha…

cs.CL2021

A Novel Global Feature-Oriented Relational Triple Extraction Model based on Table Filling

Feiliang Ren, Longhui Zhang, Shujuan Yin +4

Table filling based relational triple extraction methods are attracting growing research interests due to their promising performance and their abilities on extracting triples from…

cs.CL2021

A Three-Stage Learning Framework for Low-Resource Knowledge-Grounded Dialogue Generation

Shilei Liu, Xiaofeng Zhao, Bochao Li +3

Neural conversation models have shown great potentials towards generating fluent and informative responses by introducing external background knowledge. Nevertheless, it is laborio…

cs.CL2021

A Conditional Cascade Model for Relational Triple Extraction

Feiliang Ren, Longhui Zhang, Shujuan Yin +3

Tagging based methods are one of the mainstream methods in relational triple extraction. However, most of them suffer from the class imbalance issue greatly. Here we propose a nove…

cs.CL2021

An Effective System for Multi-format Information Extraction

Yaduo Liu, Longhui Zhang, Shujuan Yin +2

The multi-format information extraction task in the 2021 Language and Intelligence Challenge is designed to comprehensively evaluate information extraction from different dimension…