9 papers
Simulating Human Cognition: Heartbeat-Driven Autonomous Thinking Activity Scheduling for LLM-based AI systems
Hong Su
Large Language Model (LLM) agents have demonstrated remarkable capabilities in reasoning and tool use, yet they often suffer from rigid, reactive control flows that limit their ada…
Autonomous Question Formation for Large Language Model-Driven AI Systems
Hong Su
Large language model (LLM)-driven AI systems are increasingly important for autonomous decision-making in dynamic and open environments. However, most existing systems rely on pred…
Actively Obtaining Environmental Feedback for Autonomous Action Evaluation Without Predefined Measurements
Hong Su
Obtaining reliable feedback from the environment is a fundamental capability for intelligent agents to evaluate the correctness of their actions and to accumulate reusable knowledg…
Human-Inspired Learning for Large Language Models via Obvious Record and Maximum-Entropy Method Discovery
Hong Su
Large Language Models (LLMs) excel at extracting common patterns from large-scale corpora, yet they struggle with rare, low-resource, or previously unseen scenarios-such as niche h…
Cross-Question Method Reuse in Large Language Models: From Word-Level Prediction to Rational Logical-Layer Reasoning
Hong Su
Large language models (LLMs) have been widely applied to assist in finding solutions for diverse questions. Prior work has proposed representing a method as a pair of a question an…
A Layered Intuition -- Method Model with Scope Extension for LLM Reasoning
Hong Su
Existing studies have introduced method-based reasoning and scope extension as approaches to enhance Large Language Model (LLM) performance beyond direct matrix mappings. Building…