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cs.CL2025
SEVADE: Self-Evolving Multi-Agent Analysis with Decoupled Evaluation for Hallucination-Resistant Irony Detection
Ziqi Liu, Ziyang Zhou, Yilin Li +4
Sarcasm detection is a crucial yet challenging Natural Language Processing task. Existing Large Language Model methods are often limited by single-perspective analysis, static reas…
cs.CL2025
CAF-I: A Collaborative Multi-Agent Framework for Enhanced Irony Detection with Large Language Models
Ziqi. Liu, Ziyang. Zhou, Mingxuan. Hu
Large language model (LLM) have become mainstream methods in the field of sarcasm detection. However, existing LLM methods face challenges in irony detection, including: 1. single-…