22 citations · 30 across the 8 of their papers we have counts for
8 papers
Learning from Semi-Factuals: A Debiased and Semantic-Aware Framework for Generalized Relation Discovery
Jiaxin Wang, Lingling Zhang, Jun Liu +2
We introduce a novel task, called Generalized Relation Discovery (GRD), for open-world relation extraction. GRD aims to identify unlabeled instances in existing pre-defined relatio…
Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text
Fangzhi Xu, Jun Liu, Qika Lin +3
Logical reasoning task involves diverse types of complex reasoning over text, based on the form of multiple-choice question answering. Given the context, question and a set of opti…
GPTR: Gestalt-Perception Transformer for Diagram Object Detection
Xin Hu, Lingling Zhang, Jun Liu +3
Diagram object detection is the key basis of practical applications such as textbook question answering. Because the diagram mainly consists of simple lines and color blocks, its v…
Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning
Fangzhi Xu, Jun Liu, Qika Lin +2
Machine reading comprehension has aroused wide concerns, since it explores the potential of model for text understanding. To further equip the machine with the reasoning capability…
Learning First-Order Rules with Relational Path Contrast for Inductive Relation Reasoning
Yudai Pan, Jun Liu, Lingling Zhang +3
Relation reasoning in knowledge graphs (KGs) aims at predicting missing relations in incomplete triples, whereas the dominant paradigm is learning the embeddings of relations and e…
RL-CSDia: Representation Learning of Computer Science Diagrams
Shaowei Wang, LingLing Zhang, Xuan Luo +3
Recent studies on computer vision mainly focus on natural images that express real-world scenes. They achieve outstanding performance on diverse tasks such as visual question answe…