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Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification
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This method introduces a novel multi-stage pipeline for zero-shot object state classification. It synergistically integrates LLM-generated domain-specific knowledge, fuses it with general-purpose embeddings, and then leverages Knowledge Graphs and Graph Neural Networks to project these combined semantic embeddings into a visual space. This unified framework enables effective reasoning by combining LLM-derived knowledge and KG structure to solve a complex vision task.
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