activity
20242026
collaborators

5 papers

cs.LG2026

COPE: Continual Personalization of LLMs under Sparse User Feedback via User Embeddings and Self-Evaluation

Ruike Cao, Fugen Yao, Liang Dong +3

While Large Language Models (LLMs) have achieved remarkable results across various benchmarks, their alignment with normative values often results in homogenized responses that fai…

cs.AI2025

Sound Scene Synthesis at the DCASE 2024 Challenge

Mathieu Lagrange, Junwon Lee, Modan Tailleur +5

This paper presents Task 7 at the DCASE 2024 Challenge: sound scene synthesis. Recent advances in sound synthesis and generative models have enabled the creation of realistic and d…

cs.SD2024

Challenge on Sound Scene Synthesis: Evaluating Text-to-Audio Generation

Junwon Lee, Modan Tailleur, Laurie M. Heller +5

Despite significant advancements in neural text-to-audio generation, challenges persist in controllability and evaluation. This paper addresses these issues through the Sound Scene…

cs.SD2024

Correlation of Fréchet Audio Distance With Human Perception of Environmental Audio Is Embedding Dependant

Modan Tailleur, Junwon Lee, Mathieu Lagrange +4

This paper explores whether considering alternative domain-specific embeddings to calculate the Fréchet Audio Distance (FAD) metric can help the FAD to correlate better with percep…

cs.SD2024

Detection of Deepfake Environmental Audio

Hafsa Ouajdi, Oussama Hadder, Modan Tailleur +2

With the ever-rising quality of deep generative models, it is increasingly important to be able to discern whether the audio data at hand have been recorded or synthesized. Althoug…