HALO, a three-tier hierarchical multi-agent LLM framework with MCTS workflow search and prompt refinement, reports 78.6% average accuracy on HumanEval, MMLU, and MATH, beating six baselines by 14.6 percentage points.
Ai-vqa: visual question answering based on agent interaction with interpretability,
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HALO: Hierarchical Autonomous Logic-Oriented Orchestration for Multi-Agent LLM Systems
HALO, a three-tier hierarchical multi-agent LLM framework with MCTS workflow search and prompt refinement, reports 78.6% average accuracy on HumanEval, MMLU, and MATH, beating six baselines by 14.6 percentage points.