6 papers
Poller: Are LLMs Suitable for Evaluating the Poetry Understanding Task?
Shanshan Wang, Derek F. Wong, Jingming Yao +1
Traditional automatic evaluation methods have been shown to be unsuitable for modern Chinese poetry because of the distinct nature of this literary genre. Human evaluation remains…
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…
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…
Who Wrote This Line? Evaluating the Detection of LLM-Generated Classical Chinese Poetry
Jiang Li, Tian Lan, Shanshan Wang +5
The rapid development of large language models (LLMs) has extended text generation tasks into the literary domain. However, AI-generated literary creations has raised increasingly…
Can ChatGPT Really Understand Modern Chinese Poetry?
Shanshan Wang, Derek F. Wong, Jingming Yao +1
ChatGPT has demonstrated remarkable capabilities on both poetry generation and translation, yet its ability to truly understand poetry remains unexplored. Previous poetry-related w…
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…