TY - GEN
T1 - Arc Loss
T2 - 15th Asia Information Retrieval Societies Conference, AIRS 2019
AU - Suzuki, Rikiya
AU - Fujita, Sumio
AU - Sakai, Tetsuya
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Answer retrieval
KW - Question answering
KW - Representation learning
UR - http://www.scopus.com/inward/record.url?scp=85082395205&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85082395205&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-42835-8_4
DO - 10.1007/978-3-030-42835-8_4
M3 - Conference contribution
AN - SCOPUS:85082395205
SN - 9783030428341
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 34
EP - 40
BT - Information Retrieval Technology - 15th Asia Information Retrieval Societies Conference, AIRS 2019, Proceedings
A2 - Wang, Fu Lee
A2 - Xie, Haoran
A2 - Lam, Wai
A2 - Sun, Aixin
A2 - Ku, Lun-Wei
A2 - Hao, Tianyong
A2 - Chen, Wei
A2 - Wong, Tak-Lam
A2 - Tao, Xiaohui
PB - Springer
Y2 - 7 November 2019 through 9 November 2019
ER -