A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Alexandria Leto, Cecilia Aguerrebere, I. Bhati, et al.
This paper investigates how retrieval accuracy affects RAG pipeline performance for QA tasks, finding that lowering search accuracy minimally impacts downstream quality while improving speed and memory.
Keyan Cao, Yefan Liu, Gongjie Meng, et al.
This paper reviews edge computing as a new paradigm for local data processing near the network edge, addressing cloud computing limitations in IoE scenarios.
Yue‐Jiao Gong, Jingjing Li, Yicong Zhou, et al.
Proposes GL-PSO, a hybrid PSO-GA algorithm that uses genetic evolution to breed high-quality exemplars for particle swarm optimization, enhancing global search and efficiency.
Laurianne David, Amol Thakkar, Rocío Mercado, et al.
This review catalogs molecular representations for AI-driven drug discovery, serving as a practical guide for researchers new to chemical syntax.
Richard C. Mohs, Nigel H. Greig
This paper outlines the drug discovery and development process to help basic scientists frame their research for effective translation to clinical use.
Scott Thiebes, Sebastian Lins, Ali Sunyaev
Introduces Trustworthy AI (TAI) with five foundational principles and a data-driven research framework for future AI governance.
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.
Michael Dowling, Brian M. Lucey
ChatGPT can assist finance research by generating ideas and identifying data, but is weaker on literature synthesis and testing frameworks, with output quality depending on private data and domain expertise.
Tri Nguyen, Risto Katila, Tuan Nguyen Gia
This paper studies the feasibility of an Internet-of-Drones system using blockchain and AI at the edge to improve search and rescue quality of service.
Thomas Philip Rúnarsson, Xin Yao
Introduces stochastic ranking to balance objective and penalty functions in constrained evolutionary optimization, improving search performance without specialized variation operators.
David Lewis, Yiming Yang, Tony Rose, et al.
This paper introduces RCV1, a large-scale benchmark of over 800,000 categorized newswire stories for text categorization, detailing its coding policy, taxonomy semantics, and corrections, while providing baseline results for supervised learning metho
Jialong Li, Mingyue Zhang, Nianyu Li, et al.
This paper surveys the potential benefits and challenges of using generative AI, particularly LLMs, to enhance self-adaptive systems, and outlines a research roadmap.