321 citations · 420 across the 20 of their papers we have counts for
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Weakly supervised concept Bottleneck Learning for Robust Two stage Object centric visual reasoning
Sparsh Tiwari, Gesina Schwalbe, Bettina Finzel
Two-stage neuro-symbolic architectures provide an elegant paradigm for visual problem solving by cleanly separating connectionist perception of predefined symbols from possibly lat…
Weakly Supervised Concept Learning for Object-centric Visual Reasoning
Sparsh Tiwari, Bettina Finzel, Gesina Schwalbe
Neurosymbolic systems promise to combine deep neural network's (DNN) processing of raw sensor inputs with few-shot performance of symbolic artificial intelligence. Two-stage approa…
Explaining, Verifying, and Aligning Semantic Hierarchies in Vision-Language Model Embeddings
Gesina Schwalbe, Mert Keser, Moritz Bayerkuhnlein +8
Vision-language model (VLM) encoders such as CLIP enable strong retrieval and zero-shot classification in a shared image-text embedding space, yet the semantic organization of this…