Mingni Tang — accepted AI-conference papers

2025

NOTA: Multimodal Music Notation Understanding for Visual Large Language Model

Mingni Tang, Jiajia Li, Lu Yang, Zhiqiang Zhang, Jinhao Tian, Zuchao Li +2

NAACL 2025findings

Symbolic music is represented in two distinct forms: two-dimensional, visually intuitive score images, and one-dimensional, standardized text annotation sequences. While large language models have shown extraordinary potential in music, current research has primarily focused on unimodal symbol seque…

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2024

The Music Maestro or The Musically Challenged, A Massive Music Evaluation Benchmark for Large Language Models

Jiajia Li, Lu Yang, Mingni Tang, Chenchong Chenchong, Zuchao Li, Ping Wang +1

ACL 2024findings

Benchmark plays a pivotal role in assessing the advancements of large language models (LLMs). While numerous benchmarks have been proposed to evaluate LLMs’ capabilities, there is a notable absence of a dedicated benchmark for assessing their musical abilities. To address this gap, we present ZIQI-E…

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