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aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model.

, , , and . CIKM, page 287-296. ACM, (2016)

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Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance., , , , , and . CIKM, page 2487-2496. ACM, (2021)A Contrastive Pre-training Approach to Discriminative Autoencoder for Dense Retrieval., , , , and . CIKM, page 4314-4318. ACM, (2022)An In-Context Schema Understanding Method for Knowledge Base Question Answering., , , , , , and . CoRR, (2023)Dynamic-K Recommendation with Personalized Decision Boundary., , , and . CoRR, (2020)MatchZoo: A Learning, Practicing, and Developing System for Neural Text Matching., , , and . SIGIR, page 1297-1300. ACM, (2019)Controlling Risk of Web Question Answering., , , , and . SIGIR, page 115-124. ACM, (2019)Sparse Word Embeddings Using ℓ1 Regularized Online Learning., , , , and . IJCAI, page 2915-2921. IJCAI/AAAI Press, (2016)A Linguistic Study on Relevance Modeling in Information Retrieval., , , , , and . WWW, page 1053-1064. ACM / IW3C2, (2021)A Deep Look into Neural Ranking Models for Information Retrieval., , , , , , , , and . CoRR, (2019)DAPA: The WSDM 2019 Workshop on Deep Matching in Practical Applications., , , , , and . WSDM, page 844-845. ACM, (2019)