CIKM Short Paper: Knowing When to Correct

1. Problem Statement

At multi-million page scale, LLM-based OCR correction is constrained by cost:

• Full LLM correction costs hundreds of thousands of dollars on national archival collections.
• Many archival passages are already accurate; invoking LLMs on them introduces latency, cost, and risk of hallucinations.

Core Research Questions:

• RQ1: How closely does selective routing match the theoretical oracle ceiling, and does it outperform naive confidence thresholding?
• RQ2: How well does the regression-estimated improvement \hat{Δ}_i correlate with the true realized improvement Δ_i?
• RQ3: What is the actual operational cost saved when routing only segments predicted to benefit across various frontier LLMs?

Problem Visual Illustration

Figure 1: Typical OCR degradation in historical periodicals requiring cost-aware routing.