4 citations · 6 across the 9 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.CL2024★ 1 cited
Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding are Both the Problem
Sara Court, Micha Elsner
This work investigates the in-context learning abilities of pretrained large language models (LLMs) when instructed to translate text from a low-resource language into a high-resou…
cs.LG2024
DLPO: Diffusion Model Loss-Guided Reinforcement Learning for Fine-Tuning Text-to-Speech Diffusion Models
Jingyi Chen, Ju-Seung Byun, Micha Elsner +1
Recent advancements in generative models have sparked a significant interest within the machine learning community. Particularly, diffusion models have demonstrated remarkable capa…