15 citations · 24 across the 25 of their papers we have counts for
30 papers
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…
End-to-End Historical Music Restoration in Latent Space
Steven Cho, Junghyun Koo, Raphael Lafargue +3
Historical music restoration (HMR) has almost exclusively focused on constrained problems such as Super-Resolution or the restoration of solo pieces, under-exploring the general ta…
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…
TuneJury: An Open Metric for Improving Music Generation Preference Alignment
Yonghyun Kim, Junwon Lee, Haiwen Xia +5
We introduce TuneJury, an open, instance-level pairwise reward model for text-to-music that predicts a music preference score from a text prompt and an audio clip. The released che…
Break-the-Beat! Controllable MIDI-to-Drum Audio Synthesis
Shuyang Cui, Zhi Zhong, Qiyu Wu +9
Current methods for creating drum loop audio in digital music production, such as using one-shot samples or resampling, often demand non-trivial efforts of creators. While recent g…
MusTBench: Benchmarking and Advancing Temporal Grounding in Music LLMs
Daeyong Kwon, Qiyu Wu, Shinobu Kuriya +6
Recent Large Audio-Language Models (LALMs) have demonstrated promising abilities in understanding musical content. However, whether their responses are grounded in the correct temp…