arXiv:2608. 11452v1 Announce Type: cross Abstract: Text-to-image (T2I) models are increasingly asked to illustrate literary and cultural content, yet we cannot measure how well an image renders the meaning of a poem.
By Haoqi Hu, Tongji Luo, Li Zhang, Boning Zhou
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.
By Tian Lan, Shanshan Wang, Zehua Duo, Jiang Li, Guanglai Gao, Derek F. Wong, Xiangdong Su
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
arXiv:2609.23951v1 Announce Type: new
Abstract: Expressive speech synthesis has advanced through prosody modeling, yet generating structured poetic speech, such as haiku, remains challenging. Prior w...
By Devangi Sharma, Sophia Judicke, Glenda Tan, Conrad Schaumburg, Shinji Watanabe
arXiv:2607. 24873v1 Announce Type: new Abstract: Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts.
By Callie C. Liao, Duoduo Liao, Ellie L. Zhang
Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts. However, most existing systems follow a prompt-and-regenerate paradigm, making iterative refinement difficult because users must repeatedly recreate compositions instead of directly evolving existing musical ideas.
arXiv:2606. 12392v1 Announce Type: cross Abstract: Recently, large language models (LLMs) have achieved promising progress in the fields of classical Chinese translation and the generation of classical poetry.
By Haotao Xie
Recently, large language models (LLMs) have achieved promising progress in the fields of classical Chinese translation and the generation of classical poetry. However, domain-specific research on precise translation and affective-semantic understanding of classical poetry remains limited.
arXiv:2608. 05026v1 Announce Type: cross Abstract: High-quality annotation of artworks is essential for computational art research, yet extracting implicit semantics remains challenging due to the reliance on culturally grounded meanings and deep contextual knowledge behind the images.
By Xiaoyan Gu, Yifang Wang, Wenqing Zheng, Haozhong Liu, Yixia Zheng, Peiyi Jiang, Wenjie Ning, Wei Zhang, Wei Chen
arXiv:2502. 13207v4 Announce Type: replace-cross Abstract: Despite the increasing use of large language models for creative tasks, their outputs often lack diversity.
By Giorgio Franceschelli, Mirco Musolesi
arXiv:2508. 09860v2 Announce Type: replace Abstract: Human-aligned AI is a critical component of co-creativity, as it enables models to accurately interpret human intent and generate controllable outputs that align with design goals in collaborative content creation.
By In-Chang Baek, Seoyoung Lee, Sung-Hyun Kim, Geumhwan Hwang, KyungJoong Kim
arXiv:2608. 06751v1 Announce Type: cross Abstract: Artist-grounded image generation requires more than appending an artist name to a prompt.
By Kuan Xing, Ye Wang, Changyi Gan, Yuheng Li, Thao Nguyen, Yi Chang, Yilin Wang