Joint Models for Answer Verification in Question Answering Systems
Zeyu Zhang, Thuy Vu, Alessandro Moschitti
Abstract
This paper studies joint models for selecting correct answer sentences among the top k provided by answer sentence selection (AS2) modules, which are core components of retrievalbased Question Answering (QA) systems. Our work shows that a critical step to effectively exploiting an answer set regards modeling the interrelated information between pair of answers. For this purpose, we build a three-way multiclassifier, which decides if an answer supports, refutes, or is neutral with respect to another one. More specifically, our neural architecture integrates a state-of-the-art AS2 module with the multi-classifier, and a joint layer connecting all components. We tested our models on Wik-iQA, TREC-QA, and a real-world dataset. The results show that our models obtain the new state of the art in AS2. * Work done while the author was an intern at Amazon Alexa Claim: Joe Walsh was inducted in 2001. Ev1: As a member of the Eagles, Walsh was inducted into the Rock and Roll Hall of Fame in 1998, and into the Vocal Group Hall of Fame in 2001. Ev2: Joseph Fidler Walsh (born November 20, 1947) is an American singer songwriter, composer, multiinstrumentalist and record producer. Ev3: Walsh was awarded with the Vocal Group Hall of Fame in 2001.
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Cited by top-tier papers8
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Builds on4
- ALBERT: A Lite BERT for Self-supervised Learning of Language RepresentationsZhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel et al.ICLR 2020 · 7,418 citations
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- Fine-grained Fact Verification with Kernel Graph Attention NetworkZhenghao Liu, Chenyan Xiong, Maosong Sun, Zhiyuan LiuACL 2020 · 9 citations
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