CAF-I, a multi-agent LLM framework with context, semantic, and rhetorical agents plus a refinement evaluator, reports state-of-the-art zero-shot irony detection, averaging 76.31 Macro-F1 across four benchmarks.
University of Chicago Press (1974)
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CAF-I: A Collaborative Multi-Agent Framework for Enhanced Irony Detection with Large Language Models
CAF-I, a multi-agent LLM framework with context, semantic, and rhetorical agents plus a refinement evaluator, reports state-of-the-art zero-shot irony detection, averaging 76.31 Macro-F1 across four benchmarks.