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Shaosheng Cao

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#natural language process... Preprint Aug 2026

CNeo-Bench: Diagnosing Large Language Models on Chinese Neologisms

Chinese neologisms exploit diverse and unique linguistic mechanisms, such as phonetic substitution (e.g., 886 for ``bye-bye'') and visual character decomposition that are rare in other languages. We introduce CNeo-Bench, a benchmark of 4,759 such neologisms with reference definitions, organized into five top-level categories and nine subcategories by the linguistic mechanism behind each expression. CNeo-Bench is paired with a two-tier evaluation framework that separates whether a model can describe a neologism from whether it can operate on its underlying mechanism. Evaluating 18 LLMs, we find that Chinese neologisms remain an open challenge; most models fall below 40\% on definition generation, and on several subcategories a systematic recognition-manipulation gap emerges: models describe neologisms correctly but, in source-form restoration tasks, substitute a semantic equivalent (paraphrase) for the source form rather than producing the source form itself. A few-shot analysis on 1,058 hard items shows that in-context examples can solve many difficult cases, but leave a noticeable portion of errors remaining, indicating challenges beyond prompting alone can address.

Kaiyan Zhao, Zhongtao Miao, Zheyong Xie et al. · 0 citations
#artificial intelligence Preprint Aug 2026

MedUAG: Unified Understanding and Generation for Medical Multimodal Models

This work develops MedUAG, an end-to-end trained unified medical model that achieves strong performance across a wide array of understanding and generation tasks, establishing a competitive baseline and paving the way for next-generation medical multimodal systems.

Zijie Meng, Yuncheng Zhang, Hualiang Wang et al. · 0 citations
#artificial intelligence Preprint Aug 2026

DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning

DentAgent is introduced, an evidence-centric multi-agent framework, in which the Orchestrator coordinate five specialized agents spanning various modalities, which supports its value for broadly applicable and traceable multimodal dental reasoning, and highlights its potential as a technical foundation for population oral health assessment and management.

Zijie Meng, Xi-Wei Dai, Yixuan Tang et al. · 0 citations