Do Large Language Models Perform Well on Comprehending Poetic Logic in Modern Chinese Poetry?
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, particularly modern Chinese poetry, remains largely unexplored. The unique literary characteristics of modern Chinese poetry necessitate a distinct form of reasoning for effective comprehension. Unlike conventional texts that convey clear information, the unique "poetic logic" of modern Chinese poetry requires a holistic reasoning approach that goes beyond superficial semantic analysis to be understood. However, current evaluation paradigms largely ignore this critical dimension. To address this gap, we propose Peon...
| Authors | Tian Lan, Shanshan Wang, Zehua Duo et al. |
|---|---|
| Primary category | cs.CL |
| Published | 22 August 2026 |
| Last updated at source | 22 August 2026 |
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