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TWEETQA: A Social Media Focused Question Answering Dataset.

, , , , , , , and . ACL (1), page 5020-5031. Association for Computational Linguistics, (2019)

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A weighted multi-task joint sparse representation method for hyperspectral image classification., , , and . IGARSS, page 2446-2449. IEEE, (2016)Argo: intelligent advertising made possible from users' photos., , , and . ACM Multimedia, page 957-958. ACM, (2009)Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study., , , , , , and . CoRR, (2021)A Concrete Chinese NLP Pipeline., , , , , , , , , and 1 other author(s). HLT-NAACL, page 86-90. The Association for Computational Linguistics, (2015)Argo: intelligent advertising by mining a user's interest from his photo collections., , , , and . KDD Workshop on Data Mining and Audience Intelligence for Advertising, page 18-26. ACM, (2009)Embedding Lexical Features via Low-Rank Tensors., , , and . HLT-NAACL, page 1019-1029. The Association for Computational Linguistics, (2016)extending PySyft with N.-IID Federated Learning Benchmarkby Houda Bouraqqadi, Ayoub Berrag, Mohamed Mhaouach, Afaf Bouhoute, Khalid Fardousse, and Ismail Berrada: Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games., , , , , , , , and . Canadian AI, Canadian Artificial Intelligence Association, (2021)Do Multi-hop Readers Dream of Reasoning Chains?, , , , , and . MRQA@EMNLP, page 91-97. Association for Computational Linguistics, (2019)Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering., , , , , , , , , and 1 other author(s). MRQA@EMNLP, page 113-118. Association for Computational Linguistics, (2019)Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering., , , , , , and . MRQA@EMNLP, page 48-52. Association for Computational Linguistics, (2019)