1 code implementation • 21 Feb 2024 • Seiji Maekawa, Hayate Iso, Sairam Gurajada, Nikita Bhutani
We demonstrate the efficacy of our finer-grained metric and insights through an adaptive retrieval system that selectively employs retrieval and recall based on the frequencies of entities and relations in the question.
1 code implementation • 14 Jun 2023 • Seiji Maekawa, Yuya Sasaki, Makoto Onizuka
In response, we propose a simple yet holistic classification method A2DUG which leverages all combinations of node representations in directed and undirected graphs.
Ranked #1 on Node Classification on wiki
1 code implementation • 25 Jul 2022 • Seiji Maekawa, Yuya Sasaki, George Fletcher, Makoto Onizuka
We propose a framework that automatically transforms non-scalable GNNs into precomputation-based GNNs which are efficient and scalable for large-scale graphs.
1 code implementation • 18 Jun 2022 • Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka
We hope this work offers interesting insights for future research.
1 code implementation • 21 Sep 2018 • Seiji Maekawa, Koh Takeuch, Makoto Onizuka
We consider the clustering problem of attributed graphs.