papers

Publications (8)

physics.atom-ph2023

Motional ground-state cooling of single atoms in state-dependent optical tweezers

Christian Hölzl, Aaron Götzelmann, Moritz Wirth +3

Laser cooling of single atoms in optical tweezers is a prerequisite for neutral atom quantum computing and simulation. Resolved sideband cooling comprises a well-established method…

cs.SD2025

BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics

Lukas Rauch, Raphael Schwinger, Moritz Wirth +8

Deep learning (DL) has greatly advanced audio classification, yet the field is limited by the scarcity of large-scale benchmark datasets that have propelled progress in other domai…

cs.SD2024

Towards Deep Active Learning in Avian Bioacoustics

Lukas Rauch, Denis Huseljic, Moritz Wirth +3

Passive acoustic monitoring (PAM) in avian bioacoustics enables cost-effective and extensive data collection with minimal disruption to natural habitats. Despite advancements in co…

cs.SD2023

Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers

Lukas Rauch, Raphael Schwinger, Moritz Wirth +3

We propose a shift towards end-to-end learning in bird sound monitoring by combining self-supervised (SSL) and deep active learning (DAL). Leveraging transformer models, we aim to…

cs.CL2025

No Free Lunch in Active Learning: LLM Embedding Quality Dictates Query Strategy Success

Lukas Rauch, Moritz Wirth, Denis Huseljic +3

The advent of large language models (LLMs) capable of producing general-purpose representations lets us revisit the practicality of deep active learning (AL): By leveraging frozen…

cs.LG2023

ActiveGLAE: A Benchmark for Deep Active Learning with Transformers

Lukas Rauch, Matthias Aßenmacher, Denis Huseljic +3

Deep active learning (DAL) seeks to reduce annotation costs by enabling the model to actively query instance annotations from which it expects to learn the most. Despite extensive…