activity
20242026
collaborators

20 papers

cs.CV2026

Concept-TRAK: Understanding how diffusion models learn concepts through concept-level attribution

Yonghyun Park, Chieh-Hsin Lai, Satoshi Hayakawa +7

While diffusion models excel at image generation, their growing adoption raises critical concerns about copyright issues and model transparency. Existing attribution methods identi…

cs.SD2026

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…

cs.SD2025

SteerMusic: Enhanced Musical Consistency for Zero-shot Text-guided and Personalized Music Editing

Xinlei Niu, Kin Wai Cheuk, Jing Zhang +8

Music editing is an important step in music production, which has broad applications, including game development and film production. Most existing zero-shot text-guided editing me…

eess.AS2025

Automatic Music Mixing using a Generative Model of Effect Embeddings

Eloi Moliner, Marco A. Martínez-Ramírez, Junghyun Koo +5

Music mixing involves combining individual tracks into a cohesive mixture, a task characterized by subjectivity where multiple valid solutions exist for the same input. Existing au…

eess.AS2025

Towards Blind Data Cleaning: A Case Study in Music Source Separation

Azalea Gui, Woosung Choi, Junghyun Koo +5

The performance of deep learning models for music source separation heavily depends on training data quality. However, datasets are often corrupted by difficult-to-detect artifacts…

cs.SD2025

Improving Inference-Time Optimisation for Vocal Effects Style Transfer with a Gaussian Prior

Chin-Yun Yu, Marco A. Martínez-Ramírez, Junghyun Koo +3

Style Transfer with Inference-Time Optimisation (ST-ITO) is a recent approach for transferring the applied effects of a reference audio to an audio track. It optimises the effect p…