20 citations · 72 across the 37 of their papers we have counts for
4 papers · 1 filter
Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs
Andries Smit, Paul Duckworth, Nathan Grinsztajn +2
Recent advancements in large language models (LLMs) underscore their potential for responding to inquiries in various domains. However, ensuring that generative agents provide accu…
Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel
Kevin Eloff, Okko Räsänen, Herman A. Engelbrecht +2
Multi-agent reinforcement learning has been used as an effective means to study emergent communication between agents, yet little focus has been given to continuous acoustic commun…
On Optimal Transformer Depth for Low-Resource Language Translation
Elan van Biljon, Arnu Pretorius, Julia Kreutzer
Transformers have shown great promise as an approach to Neural Machine Translation (NMT) for low-resource languages. However, at the same time, transformer models remain difficult…
Unsupervised acoustic unit discovery for speech synthesis using discrete latent-variable neural networks
Ryan Eloff, André Nortje, Benjamin van Niekerk +7
For our submission to the ZeroSpeech 2019 challenge, we apply discrete latent-variable neural networks to unlabelled speech and use the discovered units for speech synthesis. Unsup…