arXiv — NLP / Computation & Language · · 3 min read

Towards End-to-End Multilingual Metaphor Processing: Integrating Detection, Translation, and Evaluation

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Computer Science > Computation and Language

arXiv:2608.04260 (cs)
[Submitted on 4 Aug 2026]

Title:Towards End-to-End Multilingual Metaphor Processing: Integrating Detection, Translation, and Evaluation

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Abstract:Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require reasoning beyond literal lexical meaning. Existing research has largely investigated metaphor detection, machine translation, and translation evaluation as separate tasks, while little work has explored how these components can be integrated into a unified computational framework. This PhD proposal aims to develop an end-to-end framework for multilingual metaphor processing consisting of three complementary research directions: (1) robust metaphor detection across languages, (2) metaphor-oriented translation evaluation for both human assessment and automatic quality estimation, and (3) joint modelling that connects metaphor detection with translation evaluation. The proposed research will combine linguistic theory with recent advances in large language models to develop new datasets, annotation methodologies, evaluation benchmarks, and automatic evaluation approaches for metaphor-aware machine translation. The expected outcome is a unified framework that improves both the development and evaluation of multilingual NLP systems when processing figurative language.
Comments: Scientific report on PhD thesis plans and milestones achieved (current progress)
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2608.04260 [cs.CL]
  (or arXiv:2608.04260v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2608.04260
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Lifeng Han Dr [view email]
[v1] Tue, 4 Aug 2026 22:35:36 UTC (84 KB)
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