Sebastian Lapuschkin
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
24
Venues
15
Active years
2016–2026
Best venue rank
A*
Where they publish
Papers
24 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | From Weights to Activations: Is Steering the Next Frontier of Adaptation? | Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, Michael A. Hedderich, Sebastian Lapuschkin, Wojciech Samek, Vera Schmitt |
| 2025 | ACL | FADE: Why Bad Descriptions Happen to Good Features. | Bruno Puri, Aakriti Jain, Elena Golimblevskaia, Patrick Kahardipraja, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin |
| 2025 | ICLR | Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence. | Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker, Leander Weber, Christopher J. Anders, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin |
| 2024 | AAAI | From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space. | Maximilian Dreyer, Frederik Pahde, Christopher J. Anders, Wojciech Samek, Sebastian Lapuschkin |
| 2024 | CVPR | Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression. | Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin |
| 2024 | CVPR | Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations. | Maximilian Dreyer, Reduan Achtibat, Wojciech Samek, Sebastian Lapuschkin |
| 2024 | ECCV | Pruning by Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers. | Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin |
| 2024 | ECCV | Synthetic Generation of Dermatoscopic Images with GAN and Closed-Form Factorization. | Rohan Reddy Mekala, Frederik Pahde, Simon Baur, Sneha Chandrashekar, Madeline Diep, Markus Wenzel, Eric L. Wisotzky, Galip mit Yolcu, Sebastian Lapuschkin, Jackie Ma, Peter Eisert, Mikael Lindvall, Adam A. Porter, Wojciech Samek |
| 2024 | ICML | AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers. | Reduan Achtibat, Sayed Mohammad Vakilzadeh Hatefi, Maximilian Dreyer, Aakriti Jain, Thomas Wiegand, Sebastian Lapuschkin, Wojciech Samek |
| 2023 | CBMI | XAI-based Comparison of Audio Event Classifiers with different Input Representations. | Annika Frommholz, Fabian Seipel, Sebastian Lapuschkin, Wojciech Samek, Johanna Vielhaben |
| 2023 | CVPR | Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations. | Alexander Binder, Leander Weber, Sebastian Lapuschkin, Grgoire Montavon, Klaus-Robert Mller, Wojciech Samek |
| 2023 | CVPR | Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations. | Maximilian Dreyer, Reduan Achtibat, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin |
| 2023 | CVPR | Optimizing Explanations by Network Canonization and Hyperparameter Search. | Frederik Pahde, Galip mit Yolcu, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin |
| 2023 | ETRA | Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models. | Daniel G. Krakowczyk, Paul Prasse, David R. Reich, Sebastian Lapuschkin, Tobias Scheffer, Lena A. Jger |
| 2023 | ICDM | Human-Centered Evaluation of XAI Methods. | Karam Tomotaki-Dawoud, Wojciech Samek, Peter Eisert, Sebastian Lapuschkin, Sebastian Bosse |
| 2023 | MICCAI | Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models. | Frederik Pahde, Maximilian Dreyer, Wojciech Samek, Sebastian Lapuschkin |
| 2022 | ICIP | Measurably Stronger Explanation Reliability Via Model Canonization. | Franz Motzkus, Leander Weber, Sebastian Lapuschkin |
| 2020 | ICML | ECQ | Daniel Becking, Maximilian Dreyer, Wojciech Samek, Karsten Mller, Sebastian Lapuschkin |
| 2020 | ICPR | Understanding Integrated Gradients with SmoothTaylor for Deep Neural Network Attribution. | Gary S. W. Goh, Sebastian Lapuschkin, Leander Weber, Wojciech Samek, Alexander Binder |
| 2020 | ICPR | Explanation-Guided Training for Cross-Domain Few-Shot Classification. | Jiamei Sun, Sebastian Lapuschkin, Wojciech Samek, Yunqing Zhao, Ngai-Man Cheung, Alexander Binder |
| 2020 | IJCNN | Towards Best Practice in Explaining Neural Network Decisions with LRP. | Maximilian Kohlbrenner, Alexander Bauer, Shinichi Nakajima, Alexander Binder, Wojciech Samek, Sebastian Lapuschkin |
| 2017 | ICASSP | Interpretable human action recognition in compressed domain. | Vignesh Srinivasan, Sebastian Lapuschkin, Cornelius Hellge, Klaus-Robert Mller, Wojciech Samek |
| 2016 | CVPR | Analyzing Classifiers: Fisher Vectors and Deep Neural Networks. | Sebastian Lapuschkin, Alexander Binder, Grgoire Montavon, Klaus-Robert Mller, Wojciech Samek |
| 2016 | ICANN | Layer-Wise Relevance Propagation for Neural Networks with Local Renormalization Layers. | Alexander Binder, Grgoire Montavon, Sebastian Lapuschkin, Klaus-Robert Mller, Wojciech Samek |