A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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This paper introduces a framework for reliable tool-using agents under communication constraints, focusing on control compression and reliability frontiers.
Sarkar Siddique, James C. L. Chow
This topical review highlights how machine learning and AI applications in healthcare communication, including chatbots for COVID-19 education, cancer therapy, and medical imaging, can benefit humans.
Jakub Konecný, H. B. McMahan, Felix X. Yu, et al.
This paper introduces strategies to improve communication efficiency in federated learning, including structured updates and compressed updates, reducing communication costs while maintaining model accuracy.
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This paper proposes an economical communication pipeline for LLM-based multi-agent systems, using a graph-based description of reasoning to reduce token costs while maintaining performance.
Sue H. Moon, Jing Betty Feng
This study reveals that AI-mediated negotiations mute traditional gender gaps in outcomes yet masculine-coded communication styles are rewarded, introducing recursive human-AI gender learning.
Zhaohui Yang, Mingzhe Chen, Walid Saad, et al.
Proposes an iterative algorithm to minimize total energy consumption in federated learning over wireless networks under latency constraints, achieving up to 59.5% energy reduction.
Mingzhe Chen, Zhaohui Yang, Walid Saad, et al.
Proposes a joint learning and communications framework for federated learning over wireless networks, optimizing user selection and resource allocation to minimize FL loss.
Gianni A. Di, Marco Dorigo
AntNet introduces a distributed, stigmergy-based ant colony optimization approach for adaptive routing in communications networks, outperforming six state-of-the-art algorithms.
Dezhang Kong, Shi Lin, Zhenhua Xu, et al.
A comprehensive survey of security risks in LLM-driven AI agent communication, proposing a three-class framework and analyzing protocols like MCP and A2A.
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This paper provides a comprehensive exploration of agentic AI systems, detailing their core architectural components, implementation strategies, and communication protocols.
Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang, et al.
This survey comprehensively reviews Federated Learning (FL) in mobile edge networks, covering fundamentals, challenges (communication, resource allocation, privacy), solutions, and applications for network optimization.