16 citations · 17 across the 3 of their papers we have counts for
3 papers · 1 filter
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…
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…
Annotating and Extracting Synthesis Process of All-Solid-State Batteries from Scientific Literature
Fusataka Kuniyoshi, Kohei Makino, Jun Ozawa +1
The synthesis process is essential for achieving computational experiment design in the field of inorganic materials chemistry. In this work, we present a novel corpus of the synth…