Papers Music Question Answering
“Music Question Answering” 태그가 달린 논문 7편 · 필터 해제
Dissonance Spectrum explicitly models perceptual frequency interactions for better music understanding
Conventional music representations describe acoustic energy over time and frequency but do not explicitly expose relations among simultaneous frequency components. We introduce the \emph{Dissonance Spectrum} (DS), a nonn…
Music Question AnsweringEmotion RecognitionArtistMus: A Globally Diverse, Artist-Centric Benchmark for Retrieval-Augmented Music Question Answering
Recent advances in large language models (LLMs) have transformed open-domain question answering, yet their effectiveness in music-related reasoning remains limited due to sparse music knowledge in pretraining data. While…
Open-Domain Question AnsweringMusic Question AnsweringInformation RetrievalMUST-RAG: MUSical Text Question Answering with Retrieval Augmented Generation
Recent advancements in Large language models (LLMs) have demonstrated remarkable capabilities across diverse domains. While they exhibit strong zero-shot performance on various tasks, LLMs' effectiveness in music-related…
Computational EfficiencyMusic Question AnsweringDomain AdaptationMuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models
Multimodal models that jointly process audio and language hold great promise in audio understanding and are increasingly being adopted in the music domain. By allowing users to query via text and obtain information about…
Multimodal ReasoningMultiple-choiceMusic Question AnsweringMusic Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning
Text-to-music generation (T2M-Gen) faces a major obstacle due to the scarcity of large-scale publicly available music datasets with natural language captions. To address this, we propose the Music Understanding LLaMA (MU…
Caption GenerationLarge Language ModelMultimodal Music GenerationMusic Captioning+2Listen, Think, and Understand
The ability of artificial intelligence (AI) systems to perceive and comprehend audio signals is crucial for many applications. Although significant progress has been made in this area since the development of AudioSet, m…
Language ModellingLarge Language ModelMusic Question AnsweringLLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention
We present LLaMA-Adapter, a lightweight adaption method to efficiently fine-tune LLaMA into an instruction-following model. Using 52K self-instruct demonstrations, LLaMA-Adapter only introduces 1.2M learnable parameters …
Instruction FollowingLanguage ModellingMultimodal Deep LearningMusic Question Answering+1