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Evaluating modular RAG with reasoning models
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This highlights a broader issue: reasoning models excel at abstract problem-solving, but optimizing tool usage without prior training remains an open challenge. While we couldn't see a clear advantage of reasoning-based modular RAG over traditional pipelines for the scope of our use case, the experiment did provide valuable insights into its potential and limitations. As models advance and tool usage strategies evolve, a reasoning-based modular RAG system could become a viable alternative, particularly for domains requiring dynamic, logic-intensive workflows.
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