Rida Saghir — accepted AI-conference papers

2026

Making Weak Supervision Interactive: Exploring Transfer from Sound Libraries to Passive Acoustic Monitoring Data

Novruz Mammadli, Rida Saghir, Kanwar Ammar Ali, Prathmesh Doddanawar, Thiago S. Gouvêa, Daniel Sonntag

IJCAI 2026

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

Cited by 0 Scholar ↗

2026

Visualizing and Interacting with Model Representation Space for Human-Centric Active Learning

Rida Saghir, Thiago S. Gouvêa, Daniel Sonntag

IJCAI 2026

Active learning reduces annotation effort by selecting informative samples, yet most approaches remain model-driven, offering users little control over training or support for understanding model behaviour. Human-centric active learning brings users further into the loop by introducing additional po

Cited by 0 Scholar ↗