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Passive acoustic monitoring (PAM) provides the necessary broad\u2010scale coverage, but its expansion introduces substantial computational challenges, including high soundscape variability, rarity of target species' signals relative to background noise, and multi\u2010species signal interference that can compromise classifier performance. We present an open\u2010source deep learning framework designed to improve robustness, adaptability, and domain generalization of PAM analyses for this population. Building on a beluga\u2010focused binary classifier, we implemented a dual\u2010stage model that separates signal detection from species classification and expanded the framework to a multi\u2010species context that includes killer whales (\n                    <jats:styled-content style=\"fixed-case\">\n                      <jats:italic>Orcinus orca<\/jats:italic>\n                    <\/jats:styled-content>\n                    ) and humpback whales (\n                    <jats:styled-content style=\"fixed-case\">\n                      <jats:italic>Megaptera novaeangliae<\/jats:italic>\n                    <\/jats:styled-content>\n                    ). Contrastive audio\u2010language models were used to efficiently increase annotation coverage for previously underrepresented species, while active learning enabled iterative refinement of model performance on new data. The framework was applied to PAM datasets from management and ecologically significant regions of lower Cook Inlet. Results demonstrated improved detection of rare species occurrences and increased confidence in daily beluga presence estimates, strengthening the role of PAM in informing recovery efforts and management decisions. This transferable workflow supports continued advancement of large\u2010scale, long\u2010term marine mammal monitoring programs.\n                  <\/jats:p>","DOI":"10.1111\/mms.70213","type":"journal-article","created":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T06:37:51Z","timestamp":1780900671000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Adaptive Acoustic Monitoring for Endangered Cook Inlet Beluga Whales in Complex Soundscapes"],"prefix":"10.1111","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9306-5577","authenticated-orcid":false,"given":"Manuel","family":"Castellote","sequence":"first","affiliation":[{"name":"Microsoft AI for Good Research Lab  Redmond Washington USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rahul","family":"Dodhia","sequence":"additional","affiliation":[{"name":"Microsoft AI for Good Research Lab  Redmond Washington USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6636-1173","authenticated-orcid":false,"given":"Daniela","family":"Ruiz","sequence":"additional","affiliation":[{"name":"Microsoft AI for Good Research Lab  Redmond Washington USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0439-8592","authenticated-orcid":false,"given":"Zhongqi","family":"Miao","sequence":"additional","affiliation":[{"name":"Microsoft AI for Good Research Lab  Redmond Washington USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pablo","family":"Arbelaez","sequence":"additional","affiliation":[{"name":"Center for Research and Formation in Artificial Intelligence Universidad de los Andes  Bogota Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Verena","family":"Gill","sequence":"additional","affiliation":[{"name":"Protected Resources Division NOAA Fisheries  Anchorage Alaska USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lori","family":"Polasek","sequence":"additional","affiliation":[{"name":"Marine Mammal Program, Alaska Department of Fish &amp; Game  Juneau Alaska USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan M.","family":"Lavista Ferres","sequence":"additional","affiliation":[{"name":"Microsoft AI for Good Research Lab  Redmond Washington USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,7]]},"reference":[{"key":"e_1_2_11_2_1","unstructured":"ABR Inc.2011.Pebble Project Environmental Baseline Document 2004 Through 2008."},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmars.2021.607321"},{"key":"e_1_2_11_4_1","unstructured":"Angler B. 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