TY - JOUR AU - Tian, Zhixing AU - Zhang, Yuanzhe AU - Feng, Xinwei AU - Jiang, Wenbin AU - Lyu, Yajuan AU - Liu, Kang AU - Zhao, Jun PY - 2020/04/03 Y2 - 2024/03/28 TI - Capturing Sentence Relations for Answer Sentence Selection with Multi-Perspective Graph Encoding JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 34 IS - 05 SE - AAAI Technical Track: Natural Language Processing DO - 10.1609/aaai.v34i05.6436 UR - https://ojs.aaai.org/index.php/AAAI/article/view/6436 SP - 9032-9039 AB - <p>This paper focuses on the answer sentence selection task. Unlike previous work, which only models the relation between the question and each candidate sentence, we propose Multi-Perspective Graph Encoder (MPGE) to take the relations among the candidate sentences into account and capture the relations from multiple perspectives. By utilizing MPGE as a module, we construct two answer sentence selection models which are based on traditional representation and pre-trained representation, respectively. We conduct extensive experiments on two datasets, WikiQA and SQuAD. The results show that the proposed MPGE is effective for both types of representation. Moreover, the overall performance of our proposed model surpasses the state-of-the-art on both datasets. Additionally, we further validate the robustness of our method by the adversarial examples of AddSent and AddOneSent.</p> ER -