77 citations · 238 across the 15 of their papers we have counts for
15 papers
Rethinking Loss Functions for Fact Verification
Yuta Mukobara, Yutaro Shigeto, Masashi Shimbo
We explore loss functions for fact verification in the FEVER shared task. While the cross-entropy loss is a standard objective for training verdict predictors, it fails to capture…
Action Class Relation Detection and Classification Across Multiple Video Datasets
Yuya Yoshikawa, Yutaro Shigeto, Masashi Shimbo +1
The Meta Video Dataset (MetaVD) provides annotated relations between action classes in major datasets for human action recognition in videos. Although these annotated relations ena…
Learning Decorrelated Representations Efficiently Using Fast Fourier Transform
Yutaro Shigeto, Masashi Shimbo, Yuya Yoshikawa +1
Barlow Twins and VICReg are self-supervised representation learning models that use regularizers to decorrelate features. Although these models are as effective as conventional rep…
Transductive Data Augmentation with Relational Path Rule Mining for Knowledge Graph Embedding
Yushi Hirose, Masashi Shimbo, Taro Watanabe
For knowledge graph completion, two major types of prediction models exist: one based on graph embeddings, and the other based on relation path rule induction. They have different…
Binarized Canonical Polyadic Decomposition for Knowledge Graph Completion
Koki Kishimoto, Katsuhiko Hayashi, Genki Akai +1
Methods based on vector embeddings of knowledge graphs have been actively pursued as a promising approach to knowledge graph completion.However, embedding models generate storage-i…
A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs
Katsuhiko Hayashi, Masashi Shimbo
Bilinear diagonal models for knowledge graph embedding (KGE), such as DistMult and ComplEx, balance expressiveness and computational efficiency by representing relations as diagona…