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2020 – today
- 2024
[c8]Seiji Maekawa, Hayate Iso, Sairam Gurajada, Nikita Bhutani:
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models. NAACL-HLT 2024: 5506-5521- [i6]Seiji Maekawa, Hayate Iso, Sairam Gurajada, Nikita Bhutani:
Retrieval Helps or Hurts? A Deeper Dive into the Efficacy of Retrieval Augmentation to Language Models. CoRR abs/2402.13492 (2024) - 2023
- [j2]Seiji Maekawa
, Yuya Sasaki, George Fletcher, Makoto Onizuka:
GenCAT: Generating attributed graphs with controlled relationships between classes, attributes, and topology. Inf. Syst. 115: 102195 (2023) - [i5]Seiji Maekawa, Yuya Sasaki, Makoto Onizuka:
Why Using Either Aggregated Features or Adjacency Lists in Directed or Undirected Graph? Empirical Study and Simple Classification Method. CoRR abs/2306.08274 (2023) - 2022
- [c7]Seiji Maekawa, Dan Zhang, Hannah Kim, Sajjadur Rahman, Estevam Hruschka:
Low-resource Interactive Active Labeling for Fine-tuning Language Models. EMNLP (Findings) 2022: 3230-3242 - [c6]Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka:
Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs. NeurIPS 2022 - [c5]Seiji Maekawa, Yuya Sasaki, George Fletcher, Makoto Onizuka:
GNN Transformation Framework for Improving Efficiency and Scalability. ECML/PKDD (2) 2022: 360-376 - [c4]Seiji Maekawa, Yuya Sasaki, George Fletcher, Makoto Onizuka:
Benchmarking GNNs with GenCAT Workbench. ECML/PKDD (6) 2022: 607-611 - [i4]Seiji Maekawa, Koki Noda, Yuya Sasaki, Makoto Onizuka:
Beyond Real-world Benchmark Datasets: An Empirical Study of Node Classification with GNNs. CoRR abs/2206.09144 (2022) - [i3]Seiji Maekawa, Yuya Sasaki, George Fletcher, Makoto Onizuka:
GNN Transformation Framework for Improving Efficiency and Scalability. CoRR abs/2207.12000 (2022) - 2021
- [c3]Yuya Ogawa, Seiji Maekawa, Yuya Sasaki, Yasuhiro Fujiwara, Makoto Onizuka:
Adaptive Node Embedding Propagation for Semi-supervised Classification. ECML/PKDD (2) 2021: 417-433 - [c2]Seiji Maekawa, Santi Saeyor, Takeshi Sakaki, Makoto Onizuka:
Effective Candidate Selection and Interpretable Interest Extraction for Follower Prediction on Social Media. WI/IAT 2021: 120-127 - [i2]Seiji Maekawa, Yuya Sasaki, George Fletcher, Makoto Onizuka:
GenCAT: Generating Attributed Graphs with Controlled Relationships between Classes, Attributes, and Topology. CoRR abs/2109.04639 (2021) - 2020
- [j1]Seiji Maekawa, Koh Takeuchi, Makoto Onizuka:
New Attributed Graph Clustering by Bridging Attribute and Topology Spaces. J. Inf. Process. 28: 427-435 (2020) - [c1]Hiroto Yamaguchi, Yuya Ogawa, Seiji Maekawa, Yuya Sasaki, Makoto Onizuka:
Controlling Internal Structure of Communities on Graph Generator. ASONAM 2020: 937-940
2010 – 2019
- 2018
- [i1]Seiji Maekawa, Koh Takeuchi, Makoto Onizuka:
Non-linear Attributed Graph Clustering by Symmetric NMF with PU Learning. CoRR abs/1810.00946 (2018)
Coauthor Index
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