8 citations · 17 across the 9 of their papers we have counts for
10 papers
The Fragility and Dynamics of LLM Pruning-Recovery Steps
Luis Frentzen Salim, Komang Rinartha, Chia-Chun Wu +3
Structural pruning followed by a recovery stage is the standard recipe for compressing large language models (LLMs), yet the two stages are typically designed and tuned in isolatio…
Audio synthesizer inversion in symmetric parameter spaces with approximately equivariant flow matching
Ben Hayes, Charalampos Saitis, György Fazekas
Many audio synthesizers can produce the same signal given different parameter configurations, meaning the inversion from sound to parameters is an inherently ill-posed problem. We…
Mamba-Diffusion Model with Learnable Wavelet for Controllable Symbolic Music Generation
Jincheng Zhang, György Fazekas, Charalampos Saitis
The recent surge in the popularity of diffusion models for image synthesis has attracted new attention to their potential for generation tasks in other domains. However, their appl…
Exploring Transformer-Based Music Overpainting for Jazz Piano Variations
Eleanor Row, Ivan Shanin, György Fazekas
This paper explores transformer-based models for music overpainting, focusing on jazz piano variations. Music overpainting generates new variations while preserving the melodic and…
Low-Data Classification of Historical Music Manuscripts: A Few-Shot Learning Approach
Elona Shatri, Daniel Raymond, George Fazekas
In this paper, we explore the intersection of technology and cultural preservation by developing a self-supervised learning framework for the classification of musical symbols in h…
Foundation Models for Music: A Survey
Yinghao Ma, Anders Øland, Anton Ragni +39
In recent years, foundation models (FMs) such as large language models (LLMs) and latent diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This com…
Zero-Shot Duet Singing Voices Separation with Diffusion Models
Chin-Yun Yu, Emilian Postolache, Emanuele Rodolà +1
In recent studies, diffusion models have shown promise as priors for solving audio inverse problems. These models allow us to sample from the posterior distribution of a target sig…
Fast Diffusion-GAN Model for Generating Symbolic Music with Emotions
Jincheng Zhang, György Fazekas, Charalampos Saitis
Diffusion models have shown promising results for a wide range of generative tasks with continuous data, such as image and audio synthesis. However, little progress has been made o…
Composer Style-specific Symbolic Music Generation Using Vector Quantized Discrete Diffusion Models
Jincheng Zhang, György Fazekas, Charalampos Saitis
Emerging Denoising Diffusion Probabilistic Models (DDPM) have become increasingly utilised because of promising results they have achieved in diverse generative tasks with continuo…
The Responsibility Problem in Neural Networks with Unordered Targets
Ben Hayes, Charalampos Saitis, György Fazekas
We discuss the discontinuities that arise when mapping unordered objects to neural network outputs of fixed permutation, referred to as the responsibility problem. Prior work has p…