18 citations · 42 across the 36 of their papers we have counts for
6 papers · 1 filter
Agentic Music Post-Production
Jaywon Koo, Junghyun Koo, Marco A. Martinez-Ramirez +5
We introduce MixAgent, an agentic pipeline for music post-production that follows the workflow of audio engineers to build interpretable and editable mixing plans guided by a refer…
FLOMSS: Generative Music Source Separation by Flow Matching
Shuyang Cui, Zhi Zhong, Keisuke Toyama +10
Music source separation (MSS) has been conventionally addressed by discriminative methods. Recently, flow matching has emerged as a strong generative paradigm for modeling complex…
Distilling Diffusion Score Discrepancy for Efficient Training Data Attribution
Shixuan Liu, Joan Serrà, Kin Wai Cheuk +6
Training data attribution for diffusion models aims to identify the training samples that influence a generated instance, but existing methods either require costly per-sample grad…
On the Human and Computer Alignment of Attribute-Based Music Matches
Roser Batlle-Roca, Woosung Choi, Joan Serrà +5
Recent advances in generative AI are raising ethical concerns regarding the originality of generated content and the potential replication of training data, with further implicatio…
Exploring the Design Space of Representation Learning for Audio Transformations
Sungho Lee, Marco Martínez-Ramírez, Junghyun Koo +3
Neural audio representation learning has enabled a range of content-oriented applications, but the resulting features remain limited for tasks involving audio processing. Furthermo…
LLM2Fx-Tools: Tool Calling For Music Post-Production
Seungheon Doh, Junghyun Koo, Marco A. Martínez-Ramírez +5
This paper introduces LLM2Fx-Tools, a multimodal tool-calling framework that generates executable sequences of audio effects (Fx-chain) for music post-production. LLM2Fx-Tools uses…