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cs.CL2026

G-IdiomAlign: A Gloss-Pivoted Benchmark for Cross-Lingual Idiom Alignment

Fengying Ye, Yanming Sun, Runzhe Zhan +3

Idioms are difficult to transfer across languages due to their non-compositionality and weak surface-form grounding, making literal mappings unreliable. We present G-IdiomAlign, a…

cs.CL2026

Seeing the Poem: Image-Semantic Detection of AI-Generated Modern Chinese Poetry with MLLMs

Shanshan Wang, Fengying Ye, Hanjia Lyu +6

Previous detection studies have shown that LLMs cannot be effectively used as detectors, but these studies have not addressed modern Chinese poetry. Moreover, no relevant research…

cs.CL2025

Exposing the Cracks: Vulnerabilities of Retrieval-Augmented LLM-based Machine Translation

Yanming Sun, Runzhe Zhan, Chi Seng Cheang +7

\textbf{RE}trieval-\textbf{A}ugmented \textbf{L}LM-based \textbf{M}achine \textbf{T}ranslation (REAL-MT) shows promise for knowledge-intensive tasks like idiomatic translation, but…

cs.CL2025

Probing Semantic Alignment, Lexical Invariance, and Syntactic Influence in LLM Metaphor Processing

Fengying Ye, Shanshan Wang, Lidia S. Chao +1

Large language models (LLMs) achieve strong performance on metaphor detection and interpretation tasks, yet it remains unclear what such behavioral success reveals about metaphor p…

cs.CL2025

Benchmarking the Detection of LLMs-Generated Modern Chinese Poetry

Shanshan Wang, Junchao Wu, Fengying Ye +3

The rapid development of advanced large language models (LLMs) has made AI-generated text indistinguishable from human-written text. Previous work on detecting AI-generated text ha…