{"type":"ScholarlyArticle","title":"Making Weak Supervision Interactive: Exploring Transfer from Sound Libraries to Passive Acoustic Monitoring Data","authors":[{"name":"Novruz Mammadli","slug":"novruz-mammadli","given":"Novruz","family":"Mammadli","affiliation":""},{"name":"Rida Saghir","slug":"rida-saghir","given":"Rida","family":"Saghir","affiliation":""},{"name":"Kanwar Ammar Ali","slug":"kanwar-ammar-ali","given":"Kanwar Ammar","family":"Ali","affiliation":""},{"name":"Prathmesh Doddanawar","slug":"prathmesh-doddanawar","given":"Prathmesh","family":"Doddanawar","affiliation":""},{"name":"Thiago S. Gouvêa","slug":"thiago-s-gouvea","given":"Thiago","family":"S. Gouvêa","affiliation":""},{"name":"Daniel Sonntag","slug":"daniel-sonntag","given":"Daniel","family":"Sonntag","affiliation":""}],"abstract":"Passive Acoustic Monitoring (PAM), an increasingly popular method for wildlife monitoring, generates large volumes of data whose analysis depends on instance-level annotations that are costly to obtain. Archival sound collections provide weak labels that lack temporal localisation. In prior work, we demonstrated that Multiple Instance Learning (MIL) can extract approximate event locations from weakly labelled PAM data, suggesting it may be applied to sound collection data. \r\nThis demo operationalizes that approach within an interactive workflow that connects weakly annotated sound collections to downstream PAM deployment. The system supports configurable MIL-based localisation, lightweight interactive refinement, and transfer to an independent PAM dataset.\r\nWe carried out a preliminary evaluation with an actual sound library from a museum collection and a benchmark PAM dataset. Results confirm that weakly annotated sound collections can serve as a viable training signal for downstream PAM detection and illustrate differences between alternative MIL instantiations under real transfer conditions. (Video available at https://cst.dfki.de/projects-weak-supervision-demo)","doi":"10.24963/ijcai.2026/979","url":"https://ijcai.org/proceedings/2026/979","pdf":"https://ijcai.org/proceedings/2026/0979.pdf","markdown":"https://ijcai.org/proceedings/2026/979.md","bibtex":"https://ijcai.org/proceedings/2026/bibtex/979","volume":{"slug":"2026","title":"Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2026","url":"https://ijcai.org/proceedings/2026/","year":2026,"location":"Bremen, Germany","dates":"15-21 August 2026","editors":"Diego Calvanese","isbn":"978-1-956792-09-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2026"},"section":"Demo Track","track":"Demo Track","number":979,"pages":{"first":8458,"last":8461},"keywords":["AI: Humans and AI","AI: Multidisciplinary Topics and Applications","AI: Machine Learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}