Sources
Philipp Schmid
Iteratively enhanced LLM outputs outperform @OpenAI GPT-4 Omni on AlpacaEval 2.0, MT-Bench, and FLASK! 🤯 Mixture-of-Agents (MoA) uses multiple LLMs in a layered architecture to iteratively enhance the generation quality. Mixture-of-Agents (MoA) 1️⃣ Select multiple LLMs with… https://t.co/BqfH66QwAK
The AI Timeline How did a Mixture-of-Agents method Achieves SotA performance and surpassing GPT4o on Alpaca & MT-Bench? Let's have a look at Mixture-of-Agents Enhances Large Language Model Capabilities 👇👇 https://t.co/kS63WP6WeT
Together AI Mixture of Agents—a framework that leverages the collective strengths of multiple LLMs. Each layer contains multiple agents that refine responses using outputs from the preceding layer. Together MoA achieves a score of 65.1% on AlpacaEval 2.0. https://t.co/UxA3nrUV5N https://t.co/DNeIHHGoTg
