mlsanityData to 7 Oct 2026

When Meaning Isn't Literal: Exploring Idiomatic Meaning Across Languages and Modalities

arXiv 2604.10787 ↗First posted 12 Apr 2026cs.CLcited by 3

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Abstract (arXiv)

Idiomatic reasoning, deeply intertwined with metaphor and culture, remains a blind spot for contemporary language models, whose progress skews toward surface-level lexical and semantic cues. For instance, the Bengali idiom textitforeignlanguagebengalichar"0986char"0999char"09CDchar"0997char"09C1 char"09B0 char"09ABchar"09B2 char"099Fchar"0995 (angur fol tok, ``grapes are sour''): it encodes denial-driven rationalization, yet naive models latch onto the literal fox-and-grape imagery. Addressing this oversight, we present ``Mediom,'' a multilingual, multimodal idiom corpus of 3,533 Hindi, Bengali, and Thai idioms, each paired with gold-standard explanations, cross-lingual translations, and carefully aligned text--image representations. We benchmark both large language models (textual reasoning) and vision-language models (figurative disambiguation) on Mediom, exposing systematic failures in metaphor comprehension. To mitigate these gaps, we propose ``HIDE,'' a Hinting-based Idiom Explanation framework that leverages error-feedback retrieval and targeted diagnostic cues for iterative reasoning refinement. Collectively, Mediom and HIDE establish a rigorous test bed and methodology for culturally grounded, multimodal idiom understanding embedded with reasoning hints in next-generation AI systems.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 20 of its 29 references that are in the map. First posted on arXiv 12 Apr 2026.

Builds on

20 of 29 references.

References · 20

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
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  12. 2024Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoningcited by 50
8 more
  1. 2021MERMAID: Metaphor Generation with Symbolism and Discriminative Decodingcited by 49
  2. 2025Large Language Models Are Human-Like Internallycited by 28
  3. 2024Understanding Figurative Meaning through Explainable Visual Entailmentcited by 19
  4. 2019Neural Simile Recognition with Cyclic Multitask Learning and Local Attentioncited by 18
  5. 2024A Hard Nut to Crack: Idiom Detection with Conversational Large Language Modelscited by 11
  6. 2021Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversationscited by 8
  7. 2021IBERT: Idiom Cloze-style reading comprehension with Attentioncited by 4
  8. 2022Vector Representations of Idioms in Conversational Systemscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

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  1. 2025BengaliFig: A Low-Resource Challenge for Figurative and Culturally Grounded Reasoning in Bengali
  2. 2024Comparative Study of Multilingual Idioms and Similes in Large Language Models
  3. 2025Memorization or Reasoning? Exploring the Idiom Understanding of LLMs
  4. 2025Beyond Understanding: Evaluating the Pragmatic Gap in LLMs' Cultural Processing of Figurative Language
  5. 2025Visual Puns from Idioms: An Iterative LLM-T2IM-MLLM Framework
  6. 2026BanglaMemeX: Advancing Cultural Metaphoric Image Interpretation in Bangla with a Multimodal Explainable Dataset
  7. 2026Reasoning Beyond Literal: Cross-style Multimodal Reasoning for Figurative Language Understanding
  8. 2026More Than Meets the Eye: Measuring the Semiotic Gap in Vision-Language Models via Semantic Anchorage