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cs.CL2024
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…
cs.CL2024★ 1 cited
Beyond prompt brittleness: Evaluating the reliability and consistency of political worldviews in LLMs
Tanise Ceron, Neele Falk, Ana Barić +2
Due to the widespread use of large language models (LLMs), we need to understand whether they embed a specific "worldview" and what these views reflect. Recent studies report that,…