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This paper introduces experiential intertextuality detection, using annotation-free methods including zero-shot LLM scoring to identify shared experiential echoes across French migration narratives from different routes.
This paper recasts fine-grained intertextuality extraction in Classical Chinese histories as an agentic LLM task, grounding reuse in exact character spans and a five-dimension typology, validated by expert-adjudicated benchmarks and scaled to the Twenty-Four Histories.