1 citations · 1 across the 7 of their papers we have counts for
7 papers
Continuous Cognitive Coverage for Autonomous Robots via Event-Dependent Cognitive Treatment and Learning
Hong Su
Autonomous robots continuously encounter objects, changes, and situations, and every event admitted into cognition should receive an appropriate cognitive treatment rather than rem…
Beyond Predefined Learning Objects: A Thinking-Learning Interaction Model for Up-to-Date Autonomous Robot Learning
Hong Su
Autonomous robots operating in open and changing environments cannot always rely on predefined inputs, outputs, and action routines. Although existing learning methods enable robot…
An LLM-Driven Closed-Loop Autonomous Learning Framework for Robots Facing Uncovered Tasks in Open Environments
Hong Su
Autonomous robots operating in open environments need the ability to continuously handle tasks that are not covered by predefined local methods. However, existing approaches often…
Method Decoration (DeMe): A Framework for LLM-Driven Adaptive Method Generation in Dynamic IoT Environments
Hong Su
Intelligent IoT systems increasingly rely on large language models (LLMs) to generate task-execution methods for dynamic environments. However, existing approaches lack the ability…
Active Thinking Model: A Goal-Directed Self-Improving Framework for Real-World Adaptive Intelligence
Hong Su
Real-world artificial intelligence (AI) systems are increasingly required to operate autonomously in dynamic, uncertain, and continuously changing environments. However, most exist…
Difference-Guided Reasoning: A Temporal-Spatial Framework for Large Language Models
Hong Su
Large Language Models (LLMs) are important tools for reasoning and problem-solving, while they often operate passively, answering questions without actively discovering new ones. T…
AdaResNet: Enhancing Residual Networks with Dynamic Weight Adjustment for Improved Feature Integration
Hong Su
In very deep neural networks, gradients can become extremely small during backpropagation, making it challenging to train the early layers. ResNet (Residual Network) addresses this…