Long-form song generation models continue to improve in duration, structural integrity, and acoustic complexity, making reliable aesthetic rewards increasingly important for aligning these models with human preferences. However, reward models for complete songs remain limited, and existing evaluators typically predict...
Jiabao Zhuang, Changhao Jiang, Hanchen Wang et al.· 0 citations
Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple applications (apps) to complete user instructions. However, due to the lack of dedicated benchmarks, their capabilities remain poorly understood. To address thi...
Junjie Ye, Zhuohui Sheng, Shao-Hua Liu et al.· 0 citations
Large language models (LLMs) are increasingly used in peer review at major AI conferences, yet novelty remains a persistent weak point. Existing benchmarks assess novelty as a single holistic score, making it difficult to diagnose which dimension a model misjudges or whether its evidence is faithful. We present NovGaug...
Guo-Qiang Zhang, Ke-Xin Tan, Ming Zhang et al.· 0 citations
A novel textual representation of fault trees is proposed, and a benchmark for multi-turn dialogue systems that emphasizes robust interaction in complex environments is constructed, evaluating a model's ability to assist in malfunction localization.
Yuhui Wang, Zhi-Xiong Yang, Ming Zhang et al.· arXiv.org· 0 citations
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