#agentic-learning News & Analysis

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs

SEAL introduces a two-stage semantic parsing framework that combines large language models with agentic learning to improve conversational question answering over knowledge graphs. The system self-evolves through dialog history and execution feedback without retraining, achieving state-of-the-art results on complex multi-hop reasoning and aggregation tasks while reducing computational costs.