Papers with Pareto-optimal efficiency frontier

1 papers
RAG-on-a-Diet: A Reinforcement Learning-Based Dynamic Resource Optimization Framework for RAG (2026.acl-long)

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Challenge: Existing frameworks for knowledge-intensive multi-hop question answering do not adapt to how a trajectory unfolds.
Approach: They propose a lightweight reinforcement-learning agent that treats each reasoning hop as an independent decision and selects the smallest model sufficient for it.
Outcome: The proposed agent cuts Monetary Inference Cost by 60.07% against IRCoT with only a 3.7% F1 drop and matches Adaptive-RAG’s F1 at 37.30% lower cost.

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