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A Survey on Deep Learning for Human Mobility., , , and . ACM Comput. Surv., 55 (2): 7:1-7:44 (2023)FocusQA: Open-Domain Question Answering with a Context in Focus., , , , , , , and . EMNLP (Findings), page 5195-5208. Association for Computational Linguistics, (2022)Human Mobility from theory to practice: Data, Models and Applications., , , and . WWW (Companion Volume), page 1311-1312. ACM, (2019)Learning to Rank Answer Candidates for Automatic Resolution of Crossword Puzzles., , and . CoNLL, page 39-48. ACL, (2014)A Survey on Deep Learning for Human Mobility, , , and . ACM Comput. Surv., (November 2021)Deep Gravity: enhancing mobility flows generation with deep neural networks and geographic information., , , and . CoRR, (2020)Trajectory test-train overlap in next-location prediction datasets., , , and . Mach. Learn., 112 (11): 4597-4634 (November 2023)Question Rewriting for Open-Domain Conversational QA: Best Practices and Limitations., , , , and . CIKM, page 2974-2978. ACM, (2021)Trajectory Test-Train Overlap in Next-Location Prediction Datasets., , , and . CoRR, (2022)SACRY: Syntax-based Automatic Crossword puzzle Resolution sYstem., , and . ACL (System Demonstrations), page 79-84. The Association for Computer Linguistics, (2015)