Arc Loss: Softmax with Additive Angular Margin for Answer Retrieval

Rikiya Suzuki, Sumio Fujita, Tetsuya Sakai

研究成果: Conference contribution

抜粋

Answer retrieval is a crucial step in question answering. To determine the best Q–A pair in a candidate pool, traditional approaches adopt triplet loss (i.e., pairwise ranking loss) for a meaningful distributed representation. Triplet loss is widely used to push away a negative answer from a certain question in a feature space and leads to a better understanding of the relationship between questions and answers. However, triplet loss is inefficient because it requires two steps: triplet generation and negative sampling. In this study, we propose an alternative loss function, namely, arc loss, for more efficient and effective learning than that by triplet loss. We evaluate the proposed approach on a commonly used QA dataset and demonstrate that it significantly outperforms the triplet loss baseline.

元の言語English
ホスト出版物のタイトルInformation Retrieval Technology - 15th Asia Information Retrieval Societies Conference, AIRS 2019, Proceedings
編集者Fu Lee Wang, Haoran Xie, Wai Lam, Aixin Sun, Lun-Wei Ku, Tianyong Hao, Wei Chen, Tak-Lam Wong, Xiaohui Tao
出版者Springer
ページ34-40
ページ数7
ISBN(印刷物)9783030428341
DOI
出版物ステータスPublished - 2020
イベント15th Asia Information Retrieval Societies Conference, AIRS 2019 - Kowloon, Hong Kong
継続期間: 2019 11 72019 11 9

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12004 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

Conference

Conference15th Asia Information Retrieval Societies Conference, AIRS 2019
Hong Kong
Kowloon
期間19/11/719/11/9

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Suzuki, R., Fujita, S., & Sakai, T. (2020). Arc Loss: Softmax with Additive Angular Margin for Answer Retrieval. : F. L. Wang, H. Xie, W. Lam, A. Sun, L-W. Ku, T. Hao, W. Chen, T-L. Wong, & X. Tao (版), Information Retrieval Technology - 15th Asia Information Retrieval Societies Conference, AIRS 2019, Proceedings (pp. 34-40). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 12004 LNCS). Springer. https://doi.org/10.1007/978-3-030-42835-8_4