VIVID: A Culturally Grounded Benchmark Exposing the Figurative Language Gap in Vietnamese NLP
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Abstract (arXiv)
We present VIVID (Vietnamese Idioms for Validation and Interpretation Depth), the first systematic benchmark for evaluating culturally grounded figurative language understanding in Vietnamese. VIVID comprises 1,636 idioms and proverbs annotated with five complexity traits (literal expressions, pragmatic nuances, Sino-Vietnamese terms, uncommon vocabulary, folk knowledge) and seven semantic themes. We establish an evaluation framework combining generative and discriminative tasks, proposing an LLM-as-a-Judge approach with aspect-based prompting validated against human judgment (Cohen's kappa = 0.792). Evaluating eight state-of-the-art models reveals critical gaps: Vietnamese-specialized models drastically underperform multilingual systems (VinaLLaMA-7B: 0.13 vs. GPT-4o: 2.46), and even top models achieve less than 50% of maximum scores. Notably, few-shot prompting does not universally improve performance, with GPT-4o exhibiting degradation due to stylistic overfitting. Our analysis exposes systematic failures including literal over-interpretation, lexical gaps, and pragmatic flattening, demonstrating that current models lack cultural competence for nuanced figurative interpretation. VIVID provides an essential tool for advancing figurative language understanding in culturally rich contexts.
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References · 22
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,718
- 2024A Survey on LLM-as-a-Judgecited by 1,384
- 2024From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judgecited by 480
- 2022FLUTE: Figurative Language Understanding through Textual Explanationscited by 78
- 2022Testing the Ability of Language Models to Interpret Figurative Languagecited by 67
- 2022SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embeddingcited by 36
- 2019Emotion Recognition for Vietnamese Social Media Textcited by 23
- 2024Are Large Language Models Good at Utility Judgments?cited by 22
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- 2024Pattern Recognition or Medical Knowledge? The Problem with Multiple-Choice Questions in Medicinecited by 13
- 2024Sign of the Times: Evaluating the use of Large Language Models for Idiomaticity Detectioncited by 11
- 2023VinaLLaMA: LLaMA-based Vietnamese Foundation Modelcited by 10
- 2024Creative and Context-Aware Translation of East Asian Idioms with GPT-4cited by 10
- 2024KULTURE Bench: A Benchmark for Assessing Language Model in Korean Cultural Contextcited by 8
- 2024Vi-Mistral-X: Building a Vietnamese Language Model with Advanced Continual Pre-trainingcited by 4
- 2025GreenMind: A Next-Generation Vietnamese Large Language Model for Structured and Logical Reasoningcited by 3
- 2025From Course to Skill: Evaluating LLM Performance in Curricular Analyticscited by 3
- 2025A Large-Scale Benchmark for Vietnamese Sentence Paraphrasescited by 1
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