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@omarsar0

Model Swarms Researchers from Google and UoW propose a new collaborative search algorithm to adapt LLM via swarm intelligence. A pool of LLM experts collaboratively move in the weight space and optimize a utility function representing various adaptation objectives. Top quote: "Extensive experiments demonstrate that MODEL SWARMS could flexibly adapt LLM experts to a single task, multi-task domains, reward models, as well as diverse human interests, improving over 12 model composition baselines by up to 21.0% across tasks and contexts." One interesting observation in the paper is that the collaborative search process helps to discover new skills and enables the weak-to-strong transition of experts.

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  "full_text": "Model Swarms\n\nResearchers from Google and UoW propose a new collaborative search algorithm to adapt LLM via swarm intelligence.\n\nA pool of LLM experts collaboratively move in the weight space and optimize a utility function representing various adaptation objectives.\n\nTop quote: \"Extensive experiments demonstrate that MODEL SWARMS could flexibly adapt LLM experts to a single task, multi-task domains, reward models, as well as diverse human interests, improving over 12 model composition baselines by up to 21.0% across tasks and contexts.\"\n\nOne interesting observation in the paper is that the collaborative search process helps to discover new skills and enables the weak-to-strong transition of experts.",
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