@inproceedings{park-etal-2025-fluid,
title = "{FLUID} {QA}: A Multilingual Benchmark for Figurative Language Usage in Dialogue across {E}nglish, {C}hinese, and {K}orean",
author = "Park, Seoyoon and
Choi, Hyeji and
Kim, Minseon and
An, Subin and
Wang, Xiaonan and
Choi, Gyuri and
Kim, Hansaem",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-main.1540/",
pages = "30268--30282",
ISBN = "979-8-89176-332-6",
abstract = "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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%0 Conference Proceedings
%T FLUID QA: A Multilingual Benchmark for Figurative Language Usage in Dialogue across English, Chinese, and Korean
%A Park, Seoyoon
%A Choi, Hyeji
%A Kim, Minseon
%A An, Subin
%A Wang, Xiaonan
%A Choi, Gyuri
%A Kim, Hansaem
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-332-6
%F park-etal-2025-fluid
%X 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.
%U https://aclanthology.org/2025.emnlp-main.1540/
%P 30268-30282
Markdown (Informal)
[FLUID QA: A Multilingual Benchmark for Figurative Language Usage in Dialogue across English, Chinese, and Korean](https://aclanthology.org/2025.emnlp-main.1540/) (Park et al., EMNLP 2025)
ACL
- Seoyoon Park, Hyeji Choi, Minseon Kim, Subin An, Xiaonan Wang, Gyuri Choi, and Hansaem Kim. 2025. FLUID QA: A Multilingual Benchmark for Figurative Language Usage in Dialogue across English, Chinese, and Korean. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 30268–30282, Suzhou, China. Association for Computational Linguistics.