1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid
Julius Gonsior, Tim Rieß, Anja Reusch +3
Annotating data is a time-consuming and costly task, but it is inherently required for supervised machine learning. Active Learning (AL) is an established method that minimizes hum…
cs.IR2025
Reverse-Engineering the Retrieval Process in GenIR Models
Anja Reusch, Yonatan Belinkov
Generative Information Retrieval (GenIR) is a novel paradigm in which a transformer encoder-decoder model predicts document rankings based on a query in an end-to-end fashion. Thes…
cs.LG2025★ 1 cited
MIB: A Mechanistic Interpretability Benchmark
Aaron Mueller, Atticus Geiger, Sarah Wiegreffe +20
How can we know whether new mechanistic interpretability methods achieve real improvements? In pursuit of lasting evaluation standards, we propose MIB, a Mechanistic Interpretabili…