Lucas Moeller — accepted AI-conference papers

2025

Interpretable Text Embeddings and Text Similarity Explanation: A Survey

Juri Opitz, Lucas Moeller, Andrianos Michail, Sebastian Pad{\'o}, Simon Clematide

EMNLP 2025

Text embeddings are a fundamental component in many NLP tasks, including classification, regression, clustering, and semantic search. However, despite their ubiquitous application, challenges persist in interpreting embeddings and explaining similarities between them.In this work, we provide a struc

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2023

An Attribution Method for Siamese Encoders

Lucas Moeller, Dmitry Nikolaev, Sebastian Padó

EMNLP 2023short main

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 predictions cannot be attributed to individual features, as they compare two inputs rather than processing a single one. This…

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