30 citations · 52 across the 25 of their papers we have counts for
8 papers · 1 filter
ArtistMus: A Globally Diverse, Artist-Centric Benchmark for Retrieval-Augmented Music Question Answering
Daeyong Kwon, SeungHeon Doh, Juhan Nam
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 mu…
TalkPlay-Tools: Conversational Music Recommendation with LLM Tool Calling
Seungheon Doh, Keunwoo Choi, Juhan Nam
While the recent developments in large language models (LLMs) have successfully enabled generative recommenders with natural language interactions, their recommendation behavior is…
PianoBind: A Multimodal Joint Embedding Model for Pop-piano Music
Hayeon Bang, Eunjin Choi, Seungheon Doh +1
Solo piano music, despite being a single-instrument medium, possesses significant expressive capabilities, conveying rich semantic information across genres, moods, and styles. How…
TalkPlayData 2: An Agentic Synthetic Data Pipeline for Multimodal Conversational Music Recommendation
Keunwoo Choi, Seungheon Doh, Juhan Nam
We present TalkPlayData 2, a synthetic dataset for multimodal conversational music recommendation generated by an agentic data pipeline. In the proposed pipeline, multiple large la…
MUST-RAG: MUSical Text Question Answering with Retrieval Augmented Generation
Daeyong Kwon, SeungHeon Doh, Juhan Nam
Recent advancements in Large language models (LLMs) have demonstrated remarkable capabilities across diverse domains. While they exhibit strong zero-shot performance on various tas…
Can Large Language Models Predict Audio Effects Parameters from Natural Language?
Seungheon Doh, Junghyun Koo, Marco A. Martínez-Ramírez +3
In music production, manipulating audio effects (Fx) parameters through natural language has the potential to reduce technical barriers for non-experts. We present LLM2Fx, a framew…
TALKPLAY: Multimodal Music Recommendation with Large Language Models
Seungheon Doh, Keunwoo Choi, Juhan Nam
We present TALKPLAY, a novel multimodal music recommendation system that reformulates recommendation as a token generation problem using large language models (LLMs). By leveraging…
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…