5 citations · 18 across the 11 of their papers we have counts for
4 papers · 1 filter
Boosting Object Representation Learning via Motion and Object Continuity
Quentin Delfosse, Wolfgang Stammer, Thomas Rothenbacher +2
Recent unsupervised multi-object detection models have shown impressive performance improvements, largely attributed to novel architectural inductive biases. Unfortunately, they ma…
Revision Transformers: Instructing Language Models to Change their Values
Felix Friedrich, Wolfgang Stammer, Patrick Schramowski +1
Current transformer language models (LM) are large-scale models with billions of parameters. They have been shown to provide high performances on a variety of tasks but are also pr…
Leveraging Explanations in Interactive Machine Learning: An Overview
Stefano Teso, Öznur Alkan, Wolfang Stammer +1
Explanations have gained an increasing level of interest in the AI and Machine Learning (ML) communities in order to improve model transparency and allow users to form a mental mod…
A Typology for Exploring the Mitigation of Shortcut Behavior
Felix Friedrich, Wolfgang Stammer, Patrick Schramowski +1
As machine learning models become increasingly larger, trained weakly supervised on large, possibly uncurated data sets, it becomes increasingly important to establish mechanisms f…