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A primary challenge in the field is the development of high-sensitivity techniques capable of probing species in low-signal regimes, such as single-molecule detection, spatially resolved TAS, and the tracking of short-lived intermediates. While advancements in instrumentation have pushed the physical limits of detection, extracting meaningful dynamics from noise-limited data remains a bottleneck. In this work, we propose a residual U-Net framework integrated with a spectral-temporal decoupling module, namely TS-ResUNet for denoising and reconstruction of transient maps. Quantitative evaluations demonstrate that TS-ResUNet consistently outperforms conventional algorithms and standard U-Net architectures in denoising, while maintaining high fidelity in the extracted spectral and kinetic information. Furthermore, sim-to-real transfer learning performed on experimental data sets indicates that effective adaptation is achievable with a small number of paired training data. This framework provides a robust methodology for refining low signal-to-noise ratio measurements and significantly accelerating data acquisition in ultrafast spectroscopy.<\/jats:p>","DOI":"10.1021\/acs.analchem.6c02650","type":"journal-article","created":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T21:08:29Z","timestamp":1788210509000},"page":"25700-25710","source":"Crossref","is-referenced-by-count":0,"title":["A Spectral-Temporal Decoupling Framework for the High-Fidelity\nReconstruction of Low-SNR Transient Absorption Spectra"],"prefix":"10.1021","volume":"98","author":[{"given":"Shi","family":"Li","sequence":"first","affiliation":[{"name":"Beijing Institute of Technology , , ,","place":["Beijing, China, 100081"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6298-5587","authenticated-orcid":true,"given":"Fan","family":"Xu","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology , , ,","place":["Beijing, China, 100081"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1986-790X","authenticated-orcid":true,"given":"Weiqian","family":"Zhao","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology , , ,","place":["Beijing, China, 100081"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8978-2958","authenticated-orcid":true,"given":"Yin","family":"Song","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology , , ,","place":["Beijing, China, 100081"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"2026090808074847500_cit1","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1021\/jacs.9b10533","article-title":"Ultrafast Spectroscopy: State of\nthe Art and Open Challenges","volume":"142","author":"Maiuri","year":"2020","journal-title":"J. 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