Takuma Yoneda


2018

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UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)
Takuma Yoneda | Jeff Mitchell | Johannes Welbl | Pontus Stenetorp | Sebastian Riedel
Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)

In this paper we describe our 2nd place FEVER shared-task system that achieved a FEVER score of 62.52% on the provisional test set (without additional human evaluation), and 65.41% on the development set. Our system is a four stage model consisting of document retrieval, sentence retrieval, natural language inference and aggregation. Retrieval is performed leveraging task-specific features, and then a natural language inference model takes each of the retrieved sentences paired with the claimed fact. The resulting predictions are aggregated across retrieved sentences with a Multi-Layer Perceptron, and re-ranked corresponding to the final prediction.

2017

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Bib2vec: Embedding-based Search System for Bibliographic Information
Takuma Yoneda | Koki Mori | Makoto Miwa | Yutaka Sasaki
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics

We propose a novel embedding model that represents relationships among several elements in bibliographic information with high representation ability and flexibility. Based on this model, we present a novel search system that shows the relationships among the elements in the ACL Anthology Reference Corpus. The evaluation results show that our model can achieve a high prediction ability and produce reasonable search results.