4 papers
Explaining Caption-Image Interactions in CLIP Models with Second-Order Attributions
Lucas Möller, Pascal Tilli, Ngoc Thang Vu +1
Dual encoder architectures like Clip models map two types of inputs into a shared embedding space and predict similarities between them. Despite their wide application, it is, howe…
Approximate Attributions for Off-the-Shelf Siamese Transformers
Lucas Möller, Dmitry Nikolaev, Sebastian Padó
Siamese encoders such as sentence transformers are among the least understood deep models. Established attribution methods cannot tackle this model class since it compares two inpu…
An Attribution Method for Siamese Encoders
Lucas Möller, Dmitry Nikolaev, Sebastian Padó
Despite the success of Siamese encoder models such as sentence transformers (ST), little is known about the aspects of inputs they pay attention to. A barrier is that their predict…
Understanding the Relation of User and News Representations in Content-Based Neural News Recommendation
Lucas Möller, Sebastian Padó
A number of models for neural content-based news recommendation have been proposed. However, there is limited understanding of the relative importances of the three main components…