The Bayesian optimization loop operates as a multi-round feedback cycle where an acquisition policy selects competing claims, generates candidate snippet edits, evaluates them against competitor items via an LLM re-ranker, and updates each claim's posterior win probability.
flowchart LR
A[Seeder: Generate Claims] --> B[Acquisition Policy: Select Claim]
B --> C[Ideator: Edit Snippet]
C --> D[Ranker: LLM Re-Ranking]
D --> E{Rank Improved?}
E -- Yes --> F[Reward = 1]
E -- No --> G[Reward = 0]
F --> H[Update Beta Posterior]
G --> H
H --> I{Halt Condition?}
I -- No --> B
I -- Yes --> J[Done: Brief & Narrative]Referenced by