Everyday we increasingly rely on machine learning models to automate and support high-stake tasks and decisions. This growing presence means that humans are now constantly interacting with machine learning-based systems, training and using models everyday. Several different techniques in computer science literature account for the human interaction with machine learning systems, but their classification is sparse and the goals varied. This survey proposes a taxonomy of Hybrid Decision Making Systems, providing both a conceptual and technical framework for understanding how current computer science literature models interaction between humans and machines.
Tree Meets Transformer: A Hybrid Architecture for Scalable Power Allocation in Cell-Free Networks
Smart Networks and Services Joint Undertaking (SNS JU)（智能网络与服务联合体）；Italian Ministry of Education and Research (MUR)（意大利教育与研究部）；HORIZON-JU-SNS-2022 EU project TIMES（HORIZON-JU-SNS-2022 EU项目TIMES）；European Union under the Italian National Recovery and Resilience Plan (NRRP) of NextGenerationEU（欧盟在意大利国家复苏与韧性计划（NRRP）下的NextGenerationEU）
Deep Learning Meets Process-Based Models: A Hybrid Approach to Agricultural Challenges
Department of Computing, and Mathematics, Faculty of Science and Engineering（计算与数学系，科学与工程学院）；Leibniz Centre for Agricultural Landscape Research (ZALF)（农业景观研究莱比锡中心（ZALF））；Institute of Crop Science and Resource Conservation (INRES)（作物科学与资源保护研究所）
When Drafts Evolve: Speculative Decoding Meets Online Learning
National Key Laboratory for Novel Software Technology, Nanjing University（南京大学新型软件技术国家重点实验室）；School of Artificial Intelligence, Nanjing University（南京大学人工智能学院）；University of California, San Diego（加州大学圣地亚哥分校）
Are Deep Learning Based Hybrid PDE Solvers Reliable? Why Training Paradigms and Update Strategies Matter
Delft Institute of Applied Mathematics（代尔夫特应用数学研究所）；Delft University of Technology（代尔夫特理工大学）；Department of Mathematics and Computer Science（数学与计算机科学系）；Eindhoven University of Technology（埃因霍温理工大学）；The Netherlands（荷兰）
ConTraNet: A single end-to-end hybrid network for EEG-based and EMG-based human machine interfaces
University hospital Knappschaftskrankenhaus Bochum GmbH（波鸿克纳普沙夫特医院有限公司大学医院）；Ruhr University Bochum（波鸿鲁尔大学）；Ruhr-West University of Applied Science（鲁尔西部应用科学大学）
