most citedSymbolic Music Loop Generation with Neural Discrete Representations

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20231 cited

Can We Utilize Pre-trained Language Models within Causal Discovery Algorithms?

Chanhui Lee, Juhyeon Kim, Yongjun Jeong +9

Scaling laws have allowed Pre-trained Language Models (PLMs) into the field of causal reasoning. Causal reasoning of PLM relies solely on text-based descriptions, in contrast to ca…

cs.LG20231 cited

Gradient Surgery for One-shot Unlearning on Generative Model

Seohui Bae, Seoyoon Kim, Hyemin Jung +1

Recent regulation on right-to-be-forgotten emerges tons of interest in unlearning pre-trained machine learning models. While approximating a straightforward yet expensive approach…

cs.SD2023

Systematic Analysis of Music Representations from BERT

Sangjun Han, Hyeongrae Ihm, Woohyung Lim

There have been numerous attempts to represent raw data as numerical vectors that effectively capture semantic and contextual information. However, in the field of symbolic music,…

cs.SD2022

Instrument Separation of Symbolic Music by Explicitly Guided Diffusion Model

Sangjun Han, Hyeongrae Ihm, DaeHan Ahn +1

Similar to colorization in computer vision, instrument separation is to assign instrument labels (e.g. piano, guitar...) to notes from unlabeled mixtures which contain only perform…

cs.SD20222 cited

Symbolic Music Loop Generation with Neural Discrete Representations

Sangjun Han, Hyeongrae Ihm, Moontae Lee +1

Since most of music has repetitive structures from motifs to phrases, repeating musical ideas can be a basic operation for music composition. The basic block that we focus on is co…