2 citations · 7 across the 14 of their papers we have counts for
8 papers · 1 filter
AnyBottle: A Recipe to Only Keep the Concepts You Really Need
Wolfgang Stammer, Sukrut Rao, Hevra Petekkaya +2
Concept bottleneck models (CBMs) make predictions inspectable and intervenable by routing them through human-interpretable concepts, but originally required concept annotations. An…
Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction
Sophia Koehler, Antonia Wüst, Inga Ibs +5
A central challenge in building intelligent systems is enabling agents to jointly perceive complex inputs, form hypotheses about hidden patterns, and design informative experiments…
Seeing Through Circuits: Faithful Mechanistic Interpretability for Vision Transformers
Nina Żukowska, Wolfgang Stammer, Bernt Schiele +1
Transparency of neural networks' internal reasoning is at the heart of interpretability research, adding to trust, safety, and understanding of these models. The field of mechanist…
Synthesizing Visual Concepts as Vision-Language Programs
Antonia Wüst, Wolfgang Stammer, Hikaru Shindo +3
Vision-Language models (VLMs) achieve strong performance on multimodal tasks but often fail at systematic visual reasoning tasks, leading to inconsistent or illogical outputs. Neur…
SLR: Automated Synthesis for Scalable Logical Reasoning
Lukas Helff, Ahmad Omar, Felix Friedrich +7
We introduce SLR, an end-to-end framework for systematic evaluation and training of Large Language Models (LLMs) via Scalable Logical Reasoning. Given a user's task specification,…
Fodor and Pylyshyn's Legacy: Still No Human-like Systematic Compositionality in Neural Networks
Tim Woydt, Moritz Willig, Antonia Wüst +4
Strong meta-learning capabilities for systematic compositionality are emerging as an important skill for navigating the complex and changing tasks of today's world. However, in pre…
Neural Concept Binder
Wolfgang Stammer, Antonia Wüst, David Steinmann +1
The challenge in object-based visual reasoning lies in generating concept representations that are both descriptive and distinct. Achieving this in an unsupervised manner requires…
Pix2Code: Learning to Compose Neural Visual Concepts as Programs
Antonia Wüst, Wolfgang Stammer, Quentin Delfosse +2
The challenge in learning abstract concepts from images in an unsupervised fashion lies in the required integration of visual perception and generalizable relational reasoning. Mor…