arXiv AI

Jiuge-Tuiqiao: An Interpretable Human-AI System for Classical Chinese Poetry Refinement

arXiv Computation and Language
Aug 25

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

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
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
Hugging Face Trending Papers
Jul 27

MusiChat: Vibe Composing for Music Creation

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 AI
Aug 6

ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation

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 AI
Jul 20

Human-Aligned Procedural Level Generation Reinforcement Learning via Text-Level-Sketch Shared Representation

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