Presentation slides

Speaker Note: Cost-Aware Human-LLM Collaboration for Post-OCR Corrections in Swiss Historical Newspapers (DocEng 2026, 28.08.2026). Presented by Stergios Konstantinidis, Hayman Lotfy, Prof. Michalis Vlachos.

Speaker Note: Building RAG systems for historical archives across 300+ years of newspapers, millions of pages, and 12 TB of raw high-resolution scan imagery.

Speaker Note: Post-OCR correction is essential for downstream retrieval, but traditional tools neglect historical linguistic shifts and archaic orthography.

Speaker Note: Different segments benefit very differently: Segment D gains +2.0% CER improvement with zero overcorrections, while Segment B suffers -3.0% CER degradation due to 10 overcorrections!

Speaker Note: Theoretical premise: What if we knew in advance which archival documents would benefit most from LLM correction?

Speaker Note: In reality, ground truth is unavailable. Naively correcting all documents produces unpredictable degradation and wastes massive token budgets.

Speaker Note: A machine-learned Router evaluating expected CER benefit: If LLM is sufficient -> route to LLM; if degradation is too severe -> route to human review (<5%); otherwise leave the segment untouched.

Speaker Note: Empirical results comparing baseline OCR, All-LLM, ConfBERT, and our Cost-Aware Routing framework across historical Swiss periodicals.

Speaker Note: Key contributions: 40% reduction in correction effort, negligible setup cost, and an effective human guardrail identifying segments requiring expert archivist attention.

Speaker Note: Wrap-up, open questions, and research collaboration contact information at UNIL-DESI.