1 citations · 1 across the 7 of their papers we have counts for
8 papers · 1 filter
Do Large Language Models Perform Well on Comprehending Poetic Logic in Modern Chinese Poetry?
Tian Lan, Shanshan Wang, Zehua Duo +4
Large Language Models (LLMs) have achieved significant progress across a wide range of natural language processing (NLP) tasks, yet their ability to understand literary texts, part…
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…
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…
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…