1 citations · 1 across the 3 of their papers we have counts for
4 papers
End-to-End Trainable Retrieval-Augmented Generation for Relation Extraction
Kohei Makino, Makoto Miwa, Yutaka Sasaki
This paper addresses a crucial challenge in retrieval-augmented generation-based relation extractors; the end-to-end training is not applicable to conventional retrieval-augmented…
Analyzing Research Trends in Inorganic Materials Literature Using NLP
Fusataka Kuniyoshi, Jun Ozawa, Makoto Miwa
In the field of inorganic materials science, there is a growing demand to extract knowledge such as physical properties and synthesis processes of materials by machine-reading a la…
A Neural Edge-Editing Approach for Document-Level Relation Graph Extraction
Kohei Makino, Makoto Miwa, Yutaka Sasaki
In this paper, we propose a novel edge-editing approach to extract relation information from a document. We treat the relations in a document as a relation graph among entities in…
Distantly Supervised Relation Extraction with Sentence Reconstruction and Knowledge Base Priors
Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou
We propose a multi-task, probabilistic approach to facilitate distantly supervised relation extraction by bringing closer the representations of sentences that contain the same Kno…