Tag: LLM agents
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Case-Based Learning Boosts Autonomous Agent Expertise
Enhance autonomous agents with case-based learning to transfer real-world expertise and improve performance on complex tasks.
GAM: Hierarchical Graph Memory Boosts LLM Agent Accuracy
Discover GAM, a hierarchical graph-based memory framework enhancing long-term reasoning and context retention in Large Language Model agents.
Context-Aware Simulation for Recommender System Testing
Discover ContextSim, a novel agent simulation framework that improves recommender system evaluation by modeling realistic user contexts and behaviors.
UniToolCall: Standardizing Tool-Use for LLM Agents
UniToolCall unifies tool-use representation, data, and evaluation to boost LLM agents' performance with over 22K tools and diverse interaction patterns.
Structured Graphs for Efficient LLM Agent Execution
Discover a scheduler-theoretic framework using structured graphs to improve LLM agent execution with better control, debugging, and reliability.