{"version":"1","article":{"id":"time-series-forecast-block-skipping-test-2026","slug":"time-series-forecast-block-skipping-test-2026","language":"en","url":"https://haberpaper.com/en/news/time-series-forecast-block-skipping-test-2026","api_url":"https://haberpaper.com/api/v1/articles/time-series-forecast-block-skipping-test-2026?lang=en","title":"Skipping some Transformer blocks cut forecasting latency in tests","summary":"A Polytechnique Montréal study tested skipping Transformer blocks during inference in Chronos-Bolt and TimesFM 2.5. Moderate skipping largely preserved forecasting quality across four benchmark datasets while lowering A100 latency.","category":"business","region":"world","topics":["ai"],"published_at":"2026-10-13T20:11:53+03:00","modified_at":"2026-10-13T20:11:53+03:00","publication_basis":"publication-record","event_period":"2026-10-09","event_period_basis":"event-or-reference-period","sources":[{"name":"arXiv, How Much Computation Does Every Forecast Need? Structured Block Skipping in Two Time-Series Foundation Models (arXiv:2610.13208)","url":"https://arxiv.org/abs/2610.13208","checkedAt":"2026-10-13","publishedAt":"2026-10-09"}],"translations":[{"language":"tr","url":"https://haberpaper.com/tr/news/time-series-forecast-block-skipping-test-2026","api_url":"https://haberpaper.com/api/v1/articles/time-series-forecast-block-skipping-test-2026?lang=tr"},{"language":"en","url":"https://haberpaper.com/en/news/time-series-forecast-block-skipping-test-2026","api_url":"https://haberpaper.com/api/v1/articles/time-series-forecast-block-skipping-test-2026?lang=en"},{"language":"ar","url":"https://haberpaper.com/ar/news/time-series-forecast-block-skipping-test-2026","api_url":"https://haberpaper.com/api/v1/articles/time-series-forecast-block-skipping-test-2026?lang=ar"},{"language":"fr","url":"https://haberpaper.com/fr/news/time-series-forecast-block-skipping-test-2026","api_url":"https://haberpaper.com/api/v1/articles/time-series-forecast-block-skipping-test-2026?lang=fr"},{"language":"es","url":"https://haberpaper.com/es/news/time-series-forecast-block-skipping-test-2026","api_url":"https://haberpaper.com/api/v1/articles/time-series-forecast-block-skipping-test-2026?lang=es"}],"data_types":[],"data":null,"data_compilations":[],"data_downloads":[],"content":{"paragraphs":["A preprint posted on arXiv on 9 October by a researcher at Polytechnique Montréal examined whether time-series forecasting needs the same computation depth for every input. The study evaluated structured masks that bypass Transformer blocks at inference in the pretrained Chronos-Bolt and TimesFM 2.5 models. Masks were chosen only on calibration windows, then tested on 1,088 held-out windows from the ETTh1, Traffic, Weather and Exchange datasets.","The author reports that, at moderate skipping levels, running seven of Chronos-Bolt’s 11 candidate blocks and 16 of TimesFM’s 20 blocks changed mean relative forecasting quality little across the datasets, while reducing median batch-one A100 latency by 11.2% and 13.4%, respectively. More aggressive skipping substantially harmed Traffic and Weather forecasts. The best block mask varied by window, but the study explicitly does not provide a deployable method for reliably choosing one for each unseen input. The findings concern two models, four datasets and the tested hardware setup; the work is a preprint that has not yet undergone peer review."],"key_points":[],"sections":[]},"text":"A Polytechnique Montréal study tested skipping Transformer blocks during inference in Chronos-Bolt and TimesFM 2.5. Moderate skipping largely preserved forecasting quality across four benchmark datasets while lowering A100 latency.\n\nA preprint posted on arXiv on 9 October by a researcher at Polytechnique Montréal examined whether time-series forecasting needs the same computation depth for every input. The study evaluated structured masks that bypass Transformer blocks at inference in the pretrained Chronos-Bolt and TimesFM 2.5 models. Masks were chosen only on calibration windows, then tested on 1,088 held-out windows from the ETTh1, Traffic, Weather and Exchange datasets.\n\nThe author reports that, at moderate skipping levels, running seven of Chronos-Bolt’s 11 candidate blocks and 16 of TimesFM’s 20 blocks changed mean relative forecasting quality little across the datasets, while reducing median batch-one A100 latency by 11.2% and 13.4%, respectively. More aggressive skipping substantially harmed Traffic and Weather forecasts. The best block mask varied by window, but the study explicitly does not provide a deployable method for reliably choosing one for each unseen input. The findings concern two models, four datasets and the tested hardware setup; the work is a preprint that has not yet undergone peer review.","corrections":[],"editorial_illustration":{"kind":"symbolic-editorial-illustration","documentary":false,"scope":"section","asset_id":"business","url":"https://haberpaper.com/assets/illustrations/business-1536.webp","width":1536,"height":1024,"alt":"Symbolic industrial workshop with machinery, a warehouse and a crane.","language":"en"},"section_illustration":{"kind":"symbolic-editorial-illustration","documentary":false,"scope":"section","asset_id":"business","url":"https://haberpaper.com/assets/illustrations/business-1536.webp","width":1536,"height":1024,"alt":"Symbolic industrial workshop with machinery, a warehouse and a crane.","language":"en"}}}