A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Zhen Tan, Dawei Li, Song Wang, et al.
This survey uniquely focuses on LLMs for data annotation, covering generation, assessment, and utilization of LLM-generated annotations.
Shubham Vatsal, Harsh Dubey
A survey of 44 papers on 39 prompt engineering methods across 29 NLP tasks, showing how structured prompts improve LLM performance without retraining.
Mohsen Soori, Behrooz Arezoo, Roza Dastres
This review surveys how AI, ML, and DL are transforming advanced robotics across autonomous navigation, cobots, manufacturing, aviation, and transportation.
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, et al.
Comprehensive survey of federated learning applications in IoT, covering services, key applications, challenges, and future directions.
William Stallings
A comprehensive textbook survey of cryptography and network security principles and practice, covering both foundational concepts and modern applications.
Fabrizio Sebastiani
This survey reviews machine learning approaches to automated text categorization, covering document representation, classifier construction, and evaluation.
Andrei Paleyes, Raoul-Gabriel Urma, Neil D. Lawrence
A survey of case studies on deploying machine learning, mapping challenges to workflow stages to set a research agenda.
Pallavi Sethi, Smruti R. Sarangi
A comprehensive survey of IoT architectures, protocols, and applications with a novel taxonomy covering technologies from sensors to applications.
John Hancock, Taghi M. Khoshgoftaar
This paper provides the first interdisciplinary survey of CatBoost for big data, covering both its strengths and weaknesses in classification and regression tasks.
Amina Adadi
This survey systematically categorizes data-efficient ML methods into four strategies: non-supervised learning, data augmentation, transfer learning, and algorithm modification.
Matteo Stefanini, Marcella Cornia, Lorenzo Baraldi, et al.
A comprehensive survey of deep learning-based image captioning, covering visual encoding, text generation, training strategies, datasets, and evaluation metrics.
Shuai Liu, Dongye Liu, Gautam Srivastava, et al.
Survey of correlation filter algorithms for real-time object tracking, covering background, key technologies, datasets, and reliability-based methods.