Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations. - Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting (CoRR, 2020)

Making deep neural networks right for the right scientific reasons by interacting with their explanations. - Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Franziska Herbert; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting (Nat. Mach. Intell., 2020)

Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions. - Xiaoting Shao; Arseny Skryagin; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (AAAI, 2021)

Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting With Their Explanations. - Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (CVPR, 2021)

SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming. - Arseny Skryagin; Wolfgang Stammer; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (CoRR, 2021)

Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. - Wolfgang Stammer; Marius Memmel; Patrick Schramowski; Kristian Kersting (CVPR, 2022)

Neural-Probabilistic Answer Set Programming. - Arseny Skryagin; Wolfgang Stammer; Daniel Ochs; Devendra Singh Dhami; Kristian Kersting (KR, 2022)

A Typology to Explore and Guide Explanatory Interactive Machine Learning. - Felix Friedrich; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (CoRR, 2022)

Revision Transformers: Getting RiT of No-Nos. - Felix Friedrich; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (CoRR, 2022)

Revision Transformers: Instructing Language Models to Change Their Values. - Felix Friedrich; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (ECAI, 2023)

Boosting Object Representation Learning via Motion and Object Continuity. - Quentin Delfosse; Wolfgang Stammer; Thomas Rothenbacher; Dwarak Vittal; Kristian Kersting (ECML/PKDD (4), 2023)

V-LoL: A Diagnostic Dataset for Visual Logical Learning. - Lukas Helff; Wolfgang Stammer; Hikaru Shindo; Devendra Singh Dhami; Kristian Kersting (CoRR, 2023)

Learning by Self-Explaining. - Wolfgang Stammer; Felix Friedrich; David Steinmann; Hikaru Shindo; Kristian Kersting (CoRR, 2023)

Leveraging explanations in interactive machine learning: An overview. - Stefano Teso; Öznur Alkan; Wolfgang Stammer; Elizabeth Daly (Frontiers Artif. Intell., 2023)

A typology for exploring the mitigation of shortcut behaviour. - Felix Friedrich; Wolfgang Stammer; Patrick Schramowski; Kristian Kersting (Nat. Mac. Intell., 2023)

Explanatory Interactive Machine Learning. - Nicolas Pfeuffer; Lorenz Baum; Wolfgang Stammer; Benjamin M. Abdel-Karim; Patrick Schramowski; Andreas M. Bucher; Christian Hügel; Gernot Rohde; Kristian Kersting; Oliver Hinz (Bus. Inf. Syst. Eng., 2023)

Learning to Intervene on Concept Bottlenecks. - David Steinmann; Wolfgang Stammer; Felix Friedrich; Kristian Kersting (ICML, 2024)

Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents. - Quentin Delfosse; Sebastian Sztwiertnia; Mark Rothermel; Wolfgang Stammer; Kristian Kersting (NeurIPS, 2024)

Neural Concept Binder. - Wolfgang Stammer; Antonia Wüst; David Steinmann; Kristian Kersting (NeurIPS, 2024)

Pix2Code: Learning to Compose Neural Visual Concepts as Programs. - Antonia Wüst; Wolfgang Stammer; Quentin Delfosse; Devendra Singh Dhami; Kristian Kersting (UAI, 2024)

Where is the Truth? The Risk of Getting Confounded in a Continual World. - Florian Peter Busch; Roshni Kamath; Rupert Mitchell; Wolfgang Stammer; Kristian Kersting; Martin Mundt (CoRR, 2024)

Learning by Self-Explaining. - Wolfgang Stammer; Felix Friedrich; David Steinmann; Manuel Brack; Hikaru Shindo; Kristian Kersting (Trans. Mach. Learn. Res., 2024)

Human-in-the-loop or AI-in-the-loop? Automate or Collaborate? - Sriraam Natarajan; Saurabh Mathur 002; Sahil Sidheekh; Wolfgang Stammer; Kristian Kersting (AAAI, 2025)

Object Centric Concept Bottlenecks. - David Steinmann; Wolfgang Stammer; Antonia Wüst; Kristian Kersting (CoRR, 2025)

Fodor and Pylyshyn's Legacy - Still No Human-like Systematic Compositionality in Neural Networks. - Tim Woydt; Moritz Willig; Antonia Wüst; Lukas Helff; Wolfgang Stammer; Constantin A. Rothkopf; Kristian Kersting (CoRR, 2025)

SLR: An Automated Synthesis Framework for Scalable Logical Reasoning. - Lukas Helff; Ahmad Omar; Felix Friedrich; Wolfgang Stammer; Antonia Wüst; Tim Woydt; Rupert Mitchell; Patrick Schramowski; Kristian Kersting (CoRR, 2025)

Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings. - Berkant Turan; Suhrab Asadulla; David Steinmann; Wolfgang Stammer; Sebastian Pokutta (CoRR, 2025)