Papers by Mingni Tang

2 papers
NOTA: Multimodal Music Notation Understanding for Visual Large Language Model (2025.findings-naacl)

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Challenge: Existing general-domain visual language models lack ability of music notation understanding . Symbolic music is represented in two distinct forms: auditory music and symbolic music .
Approach: They propose to train a multimodal music notation model using a large-scale dataset . they use cross-modal alignment to train the model for music notations analysis .
Outcome: The proposed model improves on music understanding by training with a multimodal music notation model.
The Music Maestro or The Musically Challenged, A Massive Music Evaluation Benchmark for Large Language Models (2024.findings-acl)

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Challenge: Existing benchmarks to evaluate LLMs' capabilities are inadequate for assessing their musical capabilities.
Approach: They propose to use a large-scale music benchmark specifically designed to evaluate the music-related capabilities of large language models (LLMs).
Outcome: The proposed framework evaluates 16 large language models in the domain of music.

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