-
#1AI-Oriented Programming Grammar: Rethinking Language Design for Efficient Code GenerationResearch proposing AI-oriented grammar for programming languages to reduce computational costs in LLM code generation while maintaining semantic equivalence with traditional languages.
-
#2Computational Morphology with Neural Network Approaches: A Comprehensive AnalysisReview of neural network applications in computational morphology, covering techniques, advantages, challenges, and future directions in morphological analysis and generation.
-
#3Distributed Intelligence at the Edge on IoT Networks - AETiC 2020Comprehensive analysis of distributed intelligence in IoT networks, covering edge computing architectures, applications, challenges, and future directions for intelligent IoT systems.
-
#4Introspection of Thought: A Novel AI Agent Reasoning FrameworkINoT framework enables LLMs to execute programmatic dialogue reasoning with reduced token costs and improved performance across multiple benchmarks.
-
#5Modeling Computer Network Delays Using Neural Networks: A Comprehensive AnalysisResearch paper analyzing neural network accuracy in modeling computer network delays as a function of input traffic, with practical guidelines for network modeling and optimization.
-
#6Guaranteed Quantization Error Computation for Neural Network Model CompressionResearch on computing guaranteed output errors in quantized neural networks using merged network construction and reachability analysis for model compression applications.
-
#7Beyond Token Prediction: Rethinking AI Creativity Through Battle Rap and Interactive DialogueAnalysis of token prediction limitations in creative AI, proposing interactive dialogue models for improvisational performance using battle rap as case study.
-
#8Quantum Neural Network for Soft Quantum ComputingA novel quantum neural network model using soft quantum neurons with single-qubit operations and measurements, enabling efficient nonlinear classification and noise robustness.
-
#9Token Compression Meets Compact Vision Transformers: Survey and Comparative Evaluation for Edge AIA comprehensive survey and comparative evaluation of token compression techniques for Vision Transformers, focusing on their application to compact architectures for edge AI deployment.
-
#10TREE Framework: Token-Responsive Energy Efficiency for AI-Integrated 6G NetworksAnalysis of the TREE framework, a novel energy efficiency metric for AI-integrated 6G networks that incorporates token throughput of large models as network utility.
Last updated: 2025-12-10 23:35:41