Transcribing music into a human-readable score requires a coherent understanding of rhythm, harmony, melody, and form. Two obstacles limit this goal: annotated recordings are scarce, and accurate local predictions can still produce inconsistent musical sequences. We present SheetSage2, a unified music transcription fra...
Jun-Yan Jiang, Rui-Bin Yuan, Jia-Hao Pan et al.· 0 citations
HMU-Bench, a bilingual benchmark with notation and audio components, is introduced, a bilingual benchmark with notation and audio components that motivates separate modality reporting and event-level checks for symbolic outputs.
Zhe-Qi Dai, Bo-Yang Wang, Zhi-Yue Wu et al.· 0 citations
World simulation is inherently multisensory, demanding synchronized visual and acoustic dynamics in real time. Yet prevailing interactive world models remain strictly silent, focusing exclusively on visual rendering and control while overlooking the acoustic dimension. We present HelixWorld, a real-time interactive aud...
Lei Ke, Jia-Hao Pan, Ze-Yue Tian et al.· 0 citations
This work introduces StepAudio 3 Music, a large-scale, long-form music generation model that supports explicit musical planning and open-domain text-controlled generation, and achieves the highest AudioBox Content Enjoyment, Content Usefulness, and Production Quality scores and the highest MuQ-MuLan similarity among th...
Chengli Feng, Zhi-Yue Wu, Jia-Hao Song et al.· 1 citation
Symbolic models make melody, harmony, rhythm, and form explicit but typically stop before a finished recording; audio models produce complete songs while leaving composition implicit. We introduce YuE2, which unifies symbolic and audio music generation at frontier quality through symbolic planning. A single AR-NAR Mixt...
Rui-Bin Yuan, Jia-Hao Pan, Jun-Yan Jiang et al.· 1 citation
This work proposes HDR (Hierarchical Denoising for Visual Reasoning), a unified framework that integrates hierarchical latents into causal video generation for multi-step reasoning and introduces a level-stratified multi-step video reasoning benchmark with out-of-distribution cases.
This analysis provides a structured account of current approaches to scaling LRMs beyond human supervision and the open problems involved in developing self-sustaining learning systems toward superintelligence.
Zhiqin Yang, Jing-Wen Fu, Yu-Han Liu et al.· 4 citations
This work proposes ReBind, a systematic framework that introduces semantic instructions with embedded reference tokens as the intermediate representation for multi-reference image-conditioned video editing and develops ReBind-Instruct, a specialized MLLM that learns to establish explicit bindings between visual attribu...
Xin-Yu Liu, Shi-Hao Li, Weihong Lin et al.· arXiv.org· 2 citations
Experimental results indicate that fully automated data curation combined with imbalance-aware training yields non-trivial improvements, but models still struggle to capture fine-grained acoustic features, indicating a gap between surface-level alignment and deep musical comprehension.
Zi-Ya Zhou, Shangda Wu, Shenyang Xu et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
