activity
20202023
most citedEnhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck

67 citations · 89 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CL2023★ 1 cited

Prompt2Gaussia: Uncertain Prompt-learning for Script Event Prediction

Shiyao Cui, Xin Cong, Jiawei Sheng +3

Script Event Prediction (SEP) aims to predict the subsequent event for a given event chain from a candidate list. Prior research has achieved great success by integrating external…

cs.MM2023★ 67 cited

Enhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck

Shiyao Cui, Jiangxia Cao, Xin Cong +4

This paper studies the multimodal named entity recognition (MNER) and multimodal relation extraction (MRE), which are important for multimedia social platform analysis. The core of…

cs.CV2023

The style transformer with common knowledge optimization for image-text retrieval

Wenrui Li, Zhengyu Ma, Jinqiao Shi +1

Image-text retrieval which associates different modalities has drawn broad attention due to its excellent research value and broad real-world application. However, most of the exis…

cs.LG2023

URM4DMU: an user represention model for darknet markets users

Hongmeng Liu, Jiapeng Zhao, Yixuan Huo +5

Darknet markets provide a large platform for trading illicit goods and services due to their anonymity. Learning an invariant representation of each user based on their posts on di…

cs.CL2023★ 8 cited

Event Causality Extraction with Event Argument Correlations

Shiyao Cui, Jiawei Sheng, Xin Cong +3

Event Causality Identification (ECI), which aims to detect whether a causality relation exists between two given textual events, is an important task for event causality understand…

cs.CV2022

PrUE: Distilling Knowledge from Sparse Teacher Networks

Shaopu Wang, Xiaojun Chen, Mengzhen Kou +1

Although deep neural networks have enjoyed remarkable success across a wide variety of tasks, their ever-increasing size also imposes significant overhead on deployment. To compres…

cs.CL2022

Document-Level Event Extraction via Human-Like Reading Process

Shiyao Cui, Xin Cong, Bowen Yu +3

Document-level Event Extraction (DEE) is particularly tricky due to the two challenges it poses: scattering-arguments and multi-events. The first challenge means that arguments of…

cs.CL2020★ 4 cited

Label Enhanced Event Detection with Heterogeneous Graph Attention Networks

Shiyao Cui, Bowen Yu, Xin Cong +3

Event Detection (ED) aims to recognize instances of specified types of event triggers in text. Different from English ED, Chinese ED suffers from the problem of word-trigger mismat…

cs.CL2020★ 9 cited

Edge-Enhanced Graph Convolution Networks for Event Detection with Syntactic Relation

Shiyao Cui, Bowen Yu, Tingwen Liu +3

Event detection (ED), a key subtask of information extraction, aims to recognize instances of specific event types in text. Previous studies on the task have verified the effective…