activity
20192022
most citedFEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

52 citations · 102 across the 7 of their papers we have counts for

collaborators

10 papers

cs.LG20229 cited

GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge Features

Siyang Song, Yuxin Song, Cheng Luo +7

Graph is powerful for representing various types of real-world data. The topology (edges' presence) and edges' features of a graph decides the message passing mechanism among verti…

cs.CL202210 cited

METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets

Peilin Zhou, Zeqiang Wang, Dading Chong +6

The COVID-19 pandemic continues to bring up various topics discussed or debated on social media. In order to explore the impact of pandemics on people's lives, it is crucial to und…

cs.CV2022

Scene Graph Modification as Incremental Structure Expanding

Xuming Hu, Zhijiang Guo, Yu Fu +2

A scene graph is a semantic representation that expresses the objects, attributes, and relationships between objects in a scene. Scene graphs play an important role in many cross m…

cs.CL20211 cited

Uncovering Main Causalities for Long-tailed Information Extraction

Guoshun Nan, Jiaqi Zeng, Rui Qiao +2

Information Extraction (IE) aims to extract structural information from unstructured texts. In practice, long-tailed distributions caused by the selection bias of a dataset, may le…

cs.CL202152 cited

FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

Rami Aly, Zhijiang Guo, Michael Schlichtkrull +5

Fact verification has attracted a lot of attention in the machine learning and natural language processing communities, as it is one of the key methods for detecting misinformation…

cs.CL2020

Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation

Yan Zhang, Zhijiang Guo, Zhiyang Teng +4

AMR-to-text generation is used to transduce Abstract Meaning Representation structures (AMR) into text. A key challenge in this task is to efficiently learn effective graph represe…