This paper attempts to discuss the evolution of the retrieval approaches focusing on development, challenges and future direction of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level features and to semantic features. Drive towards semantic features is due to the problem of the keywords which can be very subjective and time consuming while low level features cannot always describe high level concepts in the users' mind. Hence, introducing an interpretation inconsistency between image descriptors and high level semantics that known as the semantic gap. This paper also discusses the semantic gap issues, user query mechanisms as well as common ways used to bridge the gap in image retrieval.
SoK: Agentic Retrieval-Augmented Generation (RAG): Taxonomy, Architectures, Evaluation, and Research Directions
University of North Dakota（北达科他大学）；Youngstown State University（青年州大学）；University of Toledo（托莱多大学）；University of Missouri（密苏里大学）；Tribhuvan University（特里布文大学）
Bi-directional Training for Composed Image Retrieval via Text Prompt Learning
Australian National University（澳大利亚国立大学）；Idiap Research Institute（Idiap 研究所）；Australian Institute for Machine Learning, University of Adelaide（阿德莱德大学澳大利亚机器学习研究所）
Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval
Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Alibaba Cloud Computing（阿里云计算）；Hong Kong University of Science and Technology（香港科技大学）；University of Illinois Chicago（伊利诺伊大学芝加哥分校）
Deep Learning Techniques for Future Intelligent Cross-Media Retrieval
Namal Institute（纳马尔学院）；University of Bradford（布拉德福德大学）；Beijing University of Technology（北京工业大学）；Ghulam Ishaq Khan Institute of Engineering Sciences and Technology（古拉姆·伊沙克·汗工程科学与技术学院）；Prince Sultan University（苏丹亲王大学）；CISTER/INESC TEC（CISTER/INESC TEC 研究中心）；ISEP-IPP（波尔图理工学院高等工程学院）；Sarhad University of Science and IT（萨哈德科技大学）；Edinburgh Napier University（爱丁堡纳皮尔大学）；University of Houston（休斯顿大学）
Fair ranking: a critical review, challenges, and future directions
IIT Kharagpur（印度理工学院卡哈拉格普尔分校）；L3S Research Center（L3S研究中心）；Universitat Pompeu Fabra（庞培法布拉大学）；Competition and Markets Authority（竞争与市场管理局）；Accenture Plc（埃森哲公司）；Zalando Research（Zalando研究）；Max Planck Institute for Software Systems（马克斯·普朗克软件系统研究所）；Cornell Tech（康奈尔科技学院）
Improving Scientific Document Retrieval with Academic Concept Index
Korea University Seoul South Korea；University of Illinois Urbana-Champaign Champaign United States；Texas A\&M University College Station United States；Yonsei University Seoul South Korea；Pohang University of Science；Korea University；University of Illinois Urbana-Champaign；Texas A\&M University；Yonsei University
Robust Neural Information Retrieval: An Adversarial and Out-of-distribution Perspective
Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；University of Chinese Academy of Sciences（中国科学院大学）；University of Amsterdam（阿姆斯特丹大学）
