Adaptive Expert Selection for Complex Reasoning

Adaptive Expert Selection for Complex Reasoning

A symbolic approach to dynamically route queries to specialized LLM experts

Symbolic-MoE introduces a fine-grained expert routing system that breaks complex problems into specific skills, selecting the optimal LLM for each reasoning component.

  • Creates a symbolic representation of tasks to identify required skills
  • Dynamically routes queries to specialized LLM experts based on the identified skills
  • Achieves improved performance without requiring gradient-based training
  • Enables adaptive instance-level mixing of pre-trained models for heterogeneous reasoning tasks

Medical Impact: Enhances diagnostic reasoning by efficiently routing complex medical queries to specialized experts, improving performance on medical question answering tasks like MedMCQA and handling biomedical reasoning with greater accuracy.

Symbolic Mixture-of-Experts: Adaptive Skill-based Routing for Heterogeneous Reasoning

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