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Explain how the importance weight ratio is constructed in the Evo-GDPO clipped surrogate objective, identifying the probability distributions in its numerator and denominator.
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Dynamic Agent Scaffolding: Synthesis, Diagnostic Repair, and Evolutionary Optimization @ University of Michigan - Ann Arbor
Ch.2 Multi-Stage Harness Optimization - Dynamic Agent Scaffolding: Synthesis, Diagnostic Repair, and Evolutionary Optimization @ University of Michigan - Ann Arbor
Stage III: Evolutionary Group-Decoupled Policy Optimization - Dynamic Agent Scaffolding: Synthesis, Diagnostic Repair, and Evolutionary Optimization @ University of Michigan - Ann Arbor
Related
In the Evo-GDPO clipped surrogate policy objective, what does the reference distribution represent?
In the Evo-GDPO objective, candidate policies are rewarded solely on the basis of relative within-group ranking.
In the Evo-GDPO clipped surrogate loss formula, what specific quantity is denoted by ?
Explain how the importance weight ratio is constructed in the Evo-GDPO clipped surrogate objective, identifying the probability distributions in its numerator and denominator.
Match each mathematical component of the Evo-GDPO objective function with its role or definition.
The Evo-GDPO objective regularizes policy updates using token-level ___ divergence computed against a frozen reference checkpoint.
Order the mathematical operations performed to compute candidate 's token-level clipped surrogate term before averaging across the harness length:
How does Evo-GDPO treat Candidate A relative to Candidate B, and how does this behavior contrast with standard GRPO?