arXiv Computation and Language By Tian Lan, Shanshan Wang, Zehua Duo, Jiang Li, Guanglai Gao, Derek F. Wong, Xiangdong Su

Do Large Language Models Perform Well on Comprehending Poetic Logic in Modern Chinese Poetry?

Read the original on arXiv Computation and Language →

The paper introduces Peony, a benchmark designed to evaluate large language models’ ability to comprehend the ‘poetic logic’ of modern Chinese poetry. It defines this logic through four tasks across stanza, line, and imagery levels and tests six mainstream LLMs under both non‑thinking and thinking configurations. Results show current LLMs struggle with this literary reasoning, highlighting Peony’s role in revealing these limitations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

arXiv Computation and Language
Sep 18

Neo-Classic: A Benchmark for Evaluating Linguistic-Aesthetic Reasoning in Classical Chinese Poetry

Neo-Classic is a new benchmark designed to evaluate linguistic‑aesthetic reasoning in Classical Chinese poetry. It uses an out‑of‑sample dataset of strictly metrical poems written by contemporary experts and a set of reverse‑understanding probes, avoiding reliance on historical corpora. Experiments with leading LLMs show a 20–50% performance drop on contemporary texts and low accuracy (0–13%) on discourse‑level ordering, indicating that current models excel at local patterns but struggle with global hierarchical planning.

By Han Zhang, Zihan Gu, Zhiyuan Wang, Tianyi Ma, Jiacheng Lu, Xinyan Zhang, Yuhao Wei, Cheng Hua