most citedNotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.SD2025

Musical Score Understanding Benchmark: Evaluating Large Language Models' Comprehension of Complete Musical Scores

Congren Dai, Yue Yang, Krinos Li +12

Understanding complete musical scores entails integrated reasoning over pitch, rhythm, harmony, and large-scale structure, yet the ability of Large Language Models and Vision--Lang…

cs.SD20251 cited

NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms

Yashan Wang, Shangda Wu, Jianhuai Hu +7

We introduce NotaGen, a symbolic music generation model aiming to explore the potential of producing high-quality classical sheet music. Inspired by the success of Large Language M…

cs.SD2025

CLaMP 3: Universal Music Information Retrieval Across Unaligned Modalities and Unseen Languages

Shangda Wu, Zhancheng Guo, Ruibin Yuan +7

CLaMP 3 is a unified framework developed to address challenges of cross-modal and cross-lingual generalization in music information retrieval. Using contrastive learning, it aligns…

cs.SD2024

Exploring Tokenization Methods for Multitrack Sheet Music Generation

Yashan Wang, Shangda Wu, Xingjian Du +1

This study explores the tokenization of multitrack sheet music in ABC notation, introducing two methods--bar-stream and line-stream patching. We compare these methods against exist…

cs.SD2024

CLaMP 2: Multimodal Music Information Retrieval Across 101 Languages Using Large Language Models

Shangda Wu, Yashan Wang, Ruibin Yuan +12

Challenges in managing linguistic diversity and integrating various musical modalities are faced by current music information retrieval systems. These limitations reduce their effe…