FLUID QA: A Multilingual Benchmark for Figurative Language Usage in Dialogue across English, Chinese, and Korean
Seoyoon Park, Hyeji Choi, Minseon Kim, Subin An, Xiaonan Wang, Gyuri Choi, Hansaem Kim
摘要
Figurative language conveys stance, emotion, and social nuance, making its appropriate use essential in dialogue. While large language models (LLMs) often succeed in recognizing figurative expressions at the sentence level, their ability to use them coherently in conversation remains uncertain. We introduce FLUID QA, the first multilingual benchmark that evaluates figurative usage in dialogue across English, Korean, and Chinese. Each item embeds figurative choices into multi-turn contexts. To support interpretation, we include FLUTE-bi, a sentence-level diagnostic task. Results reveal a persistent gap: models that perform well on FLUTE-bi frequently fail on FLUID QA, especially in sarcasm and metaphor. These errors reflect systematic rhetorical confusion and limited discourse reasoning. FLUID QA provides a scalable framework for assessing usage-level figurative competence across languages.
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- MEGA: Multilingual Evaluation of Generative AIKabir Ahuja, Harshita Diddee, Rishav Hada, Millicent Ochieng 等EMNLP 2023 · 被引用 91 次
- IMPLI: Investigating NLI Models' Performance on Figurative LanguageKevin Stowe, Prasetya Ajie Utama, Iryna GurevychACL 2022 · 被引用 52 次
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- Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse PromptsXuan-Phi Nguyen, Mahani Aljunied, Shafiq Joty, Lidong BingACL 2024
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