A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Yuzhong Zhao, Yue Liu, Junpeng Liu, et al.
GMPO improves GRPO stability by replacing arithmetic mean with geometric mean of token rewards, reducing outlier sensitivity and boosting reasoning performance.
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.
Swen Hoelder, Paul A. Clarke, Paul Workman
This review outlines contemporary approaches to small molecule cancer drug discovery, emphasizing target validation, lead optimization, and biomarker-driven trials to reduce attrition and advance personalized medicine.
Jeanne Ferrante, Karl J. Ottenstein, Joe Warren
Introduces the program dependence graph (PDG) making explicit both data and control dependences for uniform optimization and incremental transformation.
Tuan-Minh Pham, Thi-Thuy-Lien Nguyen
Proposes optimization models and approximation algorithms for joint gateway placement, service placement, and routing in NFV-enabled IoT edge cloud systems.
Rashid Ali, Nurullah Shahin, Yousaf Bin Zikria, et al.
Proposes a deep reinforcement learning (Q-learning) based resource allocation mechanism (iQRA) to optimize channel observation-based MAC protocols in dense WLANs.
Luca Benini, Giovanni De Micheli
This tutorial surveys system-level design methods for energy-efficient electronic systems, covering hardware and software energy reduction across design phases.
Stefania Sardellitti, Gesualdo Scutari, Sergio Barbarossa
Jointly optimizes radio and computational resources in MIMO multicell mobile-edge computing to minimize energy consumption under latency constraints.
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.
Zongxi Li, Zijian Wang, Weiming Wang, et al.
A systematic survey of Retrieval-Augmented Generation (RAG) in education, covering workflow, retrievers, generation optimization, and applications.
Kazuki Nonoyama, Ziang Liu, Tomofumi Fujiwara, et al.
This paper optimizes energy-efficient motion planning for dual-arm industrial robots by fine-tuning PID controllers with Genetic Algorithms and Particle Swarm Optimization.
Y. Tsaig, Amir Averbuch
A method for automatic segmentation of moving objects in video sequences using graph labeling over a region adjacency graph with Markov random field optimization.