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Empirical Inference Robust Machine Learning Conference Paper Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning Reizinger*, P., Mucsányi*, B., Guo*, S., Eysenbach, B., Schölkopf, B., Brendel, W. The Fourteenth International Conference on Learning Representations (ICLR), April 2026, *equal contribution (Published) arXiv URL BibTeX
Empirical Inference Robust Machine Learning Conference Paper Cross-Entropy Is All You Need to Invert the Data Generating Process Reizinger*, P., Bizeul*, A., Juhos*, A., Vogt, J. E., Balestriero, R., Brendel, W., Klindt, D. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *Joint first authorship (Published) arXiv BibTeX
Empirical Inference Robust Machine Learning Conference Paper Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning Reizinger, P., Guo, S., Huszár, F., Schölkopf, B., Brendel, W. The Thirteenth International Conference on Learning Representations (ICLR), April 2025 (Published) arXiv BibTeX
Empirical Inference Robust Machine Learning Conference Paper Interaction Asymmetry: A General Principle for Learning Composable Abstractions Brady, J., von Kügelgen, J., Lachapelle, S., Buchholz, S., Kipf*, T., Brendel*, W. The Thirteenth International Conference on Learning Representations (ICLR), April 2025, *joint senior author (Published) arXiv BibTeX
Robust Machine Learning Conference Paper Cross-Entropy Is All You Need To Invert the Data Generating Process Reizinger, P., Bizeul, A., Juhos, A., Vogt, J. E., Balestriero, R., Brendel, W., Klindt, D. In January 2025 (Published) OpenReview BibTeX
Robust Machine Learning Conference Paper Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning Reizinger, P., Guo, S., Huszár, F., Schölkopf, B., Brendel, W. In January 2025 (Published) OpenReview BibTeX
Robust Machine Learning Conference Paper In Search of Forgotten Domain Generalization Mayilvahanan, P., Zimmermann, R. S., Wiedemer, T., Rusak, E., Juhos, A., Bethge, M., Brendel, W. In January 2025 (Published) OpenReview BibTeX
Robust Machine Learning Conference Paper Interaction Asymmetry: A General Principle for Learning Composable Abstractions Brady, J., von Kügelgen, J., Lachapelle, S., Buchholz, S., Kipf, T., Brendel, W. In January 2025 (Published) OpenReview BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Efficiently Dispatching Flash Attention For Partially Filled Attention Masks Sharma, A., Geiping, J. In ENSLP NeurIPS Workshop 2024, ENSLP NeurIPS Workshop 2024, ENSLP NeurIPS Workshop, December 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers Singh, S., Singhania, P., Ranjan, A., Kirchenbauer, J., Geiping, J., Wen, Y., Jain, N., Hans, A., Shu, M., Tomar, A., et al. International Conference for High Performance Computing, Networking, Storage and Analysis SC (SC24), 36-49, Supercomputing, IEEE Digital Library, Atlanta, GA, International Conference for High Performance Computing, November 2024 (Published) DOI URL BibTeX
Robust Machine Learning Article Interaction Asymmetry: A General Principle for Learning Composable Abstractions Brady, J., von Kügelgen, J., Lachapelle, S., Buchholz, S., Kipf, T., Brendel, W. November 2024 (Submitted) BibTeX
Safety- and Efficiency- aligned Learning Technical Report A Realistic Threat Model for Large Language Model Jailbreaks Boreiko, V., Panfilov, A., Hein, M., Geiping, J. October 2024 (Submitted) URL BibTeX
Robust Machine Learning Conference Paper Measuring Per-Unit Interpretability at Scale Without Humans Klindt, D., Zimmermann, R., Brendel, W. In September 2024 (Published) OpenReview BibTeX
Robust Machine Learning Conference Paper Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts Mészáros, A., Ujváry, S., Brendel, W., Reizinger, P., Huszár, F. In September 2024 (Published) ArXiv BibTeX
Robust Machine Learning Conference Paper InfoNCE: Identifying the Gap Between Theory and Practice Rusak, E., Reizinger, P., Juhos, A., Bringmann, O., Zimmermann, R. S., Brendel, W. In July 2024 (Published) BibTeX
Empirical Inference Robust Machine Learning Conference Paper Position: Understanding LLMs Requires More Than Statistical Generalization Reizinger, P., Ujváry, S., Mészáros, A., Kerekes, A., Brendel, W., Huszár, F. Proceedings of the 41st International Conference on Machine Learning (ICML), 235:42365-42390, Proceedings of Machine Learning Research, (Editors: Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix), PMLR, July 2024 (Published) arXiv URL BibTeX
Robust Machine Learning Conference Paper Does CLIP’s Generalization Performance Mainly Stem from High Train-Test Similarity? Mayilvahanan, P., Wiedemer, T., Rusak, E., Bethge, M., Brendel, W. In June 2024 (Published) ArXiv BibTeX
Robust Machine Learning Conference Paper Don’t trust your eyes: on the (un) reliability of feature visualizations Geirhos, R., Zimmermann, R. S., Bilodeau, B., Brendel, W., Kim, B. In June 2024 (Published) ArXiv BibTeX
Robust Machine Learning Article Translational symmetry in convolutions with localized kernels causes an implicit bias toward high frequency adversarial examples Caro, J. O., Ju, Y., Pyle, R., Dey, S., Brendel, W., Anselmi, F., Patel, A. B. Frontiers in Computational Neuroscience, 18:1387077, June 2024 (Published) Frontiers in Computational Neuroscience BibTeX
Robust Machine Learning Conference Paper An interventional perspective on identifiability in gaussian lti systems with independent component analysis Rajendran, G., Reizinger, P., Brendel, W., Ravikumar, P. K. 41-70, Causal Learning and Reasoning, March 2024 (Published) PMLR BibTeX
Robust Machine Learning Conference Paper Effective pruning of web-scale datasets based on complexity of concept clusters Abbas, A., Rusak, E., Tirumala, K., Brendel, W., Chaudhuri, K., Morcos, A. S. In January 2024 (Published) ArXiv BibTeX
Safety- and Efficiency- aligned Learning Technical Report AI Risk Management Should Incorporate Both Safety and Security Qi, X., Huang, Y., Zeng, Y., Debenedetti, E., Geiping, J., He, L., Huang, K., Madhushani, U., Sehwag, V., Shi, W., et al. 2024 BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Be like a Goldfish, Don’t Memorize! Mitigating Memorization in Generative LLMs Hans, A., Wen, Y., Jain, N., Kirchenbauer, J., Kazemi, H., Singhania, P., Singh, S., Somepalli, G., Geiping, J., Bhatele, A., et al. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems, Thirty-Eighth Annual Conference on Neural Information Processing Systems, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Bring Your Own Data! Self-Sensitivity Evaluation for Large Language Models Jain, N., Saifullah, K., Wen, Y., Kirchenbauer, J., Shu, M., Saha, A., Goldblum, M., Geiping, J., Goldstein, T. In Proceedings of the First Conference on Language Modeling, First Conference on Language Modeling, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper CALVIN: Improved Contextual Video Captioning via Instruction Tuning Somepalli, G., Chowdhury, A., Geiping, J., Basri, R., Goldstein, T., Jacobs, D. W. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems, Thirty-Eighth Annual Conference on Neural Information Processing Systems, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Technical Report Coercing LLMs to do and reveal (almost) anything Geiping, J., Stein, A., Shu, M., Saifullah, K., Wen, Y., Goldstein, T. 2024 (Submitted) URL BibTeX
Safety- and Efficiency- aligned Learning Technical Report Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion Souri, H., Bansal, A., Kazemi, H., Fowl, L., Saha, A., Geiping, J., Wilson, A. G., Chellappa, R., Goldstein, T., Goldblum, M. 2024 (Submitted) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Investigating Style Similarity in Diffusion Models Somepalli, G., Gupta, A., Gupta, K., Palta, S., Goldblum, M., Geiping, J., Shrivastava, A., Goldstein, T. In European Conference on Computer Vision (ECCV 2024), LNCS, Springer Cham, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper LMD3: Language Model Data Density Dependence Kirchenbauer, J., Honke, G., Somepalli, G., Geiping, J., Lee, K., Ippolito, D., Goldstein, T., Andre, D. In Proceedings of the First Conference on Language Modeling, First Conference on Language Modeling, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Object Recognition as Next Token Prediction Yue, K., Chen, B., Geiping, J., Li, H., Goldstein, T., Lim, S. In IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), CVPR, 2024 (Published) DOI URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper On the Reliability of Watermarks for Large Language Models Kirchenbauer, J., Geiping, J., Wen, Y., Shu, M., Saifullah, K., Kong, K., Fernando, K., Saha, A., Goldblum, M., Goldstein, T. In The Twelfth International Conference on Learning Representations, ICLR 2024, The Twelfth International Conference on Learning Representations, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models Wen, Y., Marchyok, L., Hong, S., Geiping, J., and Goldstein, T., Carlini, N. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems, Thirty-Eighth Annual Conference on Neural Information Processing Systems, 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text Hans, A., Schwarzschild, A., Cherepanova, V., Kazemi, H., Saha, A., Goldblum, M., Geiping, J., Goldstein, T. In Proceedings of Machine Learning Research, Proceedings of the Forty-First International Conference on Machine Learning , Forty-First International Conference on Machine Learning , 2024 (Published) URL BibTeX
Safety- and Efficiency- aligned Learning Conference Paper Transformers Can Do Arithmetic with the Right Embeddings McLeish, S. M., Bansal, A., Stein, A., Jain, N., Kirchenbauer, J., Bartoldson, B. R., Kailkhura, B., Bhatele, A., Geiping, J., Schwarzschild, A., et al. In Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems, Thirty-Eighth Annual Conference on Neural Information Processing Systems, 2024 (Published) URL BibTeX
Robust Machine Learning Conference Paper Provable Compositional Generalization for Object-Centric Learning Wiedemer, T., Brady, J., Panfilov, A., Juhos, A., Bethge, M., Brendel, W. In October 2023 (Published) ArXiv BibTeX
Robust Machine Learning Conference Paper Scale Alone Does not Improve Mechanistic Interpretability in Vision Models Zimmermann, R. S., Klein, T., Brendel, W. In Advances in Neural Information Processing Systems 36 (NeurIPS 2023), 57876 - 57907, Curran Associates Inc., NeurIPS, October 2023 (Published) NeurIPS Proceedings DOI URL BibTeX
Robust Machine Learning Conference Paper Compositional Generalization from First Principles Wiedemer, T., Mayilvahanan, P., Bethge, M., Brendel, W. In July 2023 (Published) NeurIPS Proceedings BibTeX
Empirical Inference Robust Machine Learning Conference Paper Desiderata for Representation Learning from Identifiability, Disentanglement, and Group-Structuredness Keurti, H., Reizinger, P., Schölkopf, B., Brendel, W. 2nd Annual Topology, Algebra, and Geometry in Machine Learning (TAG) at ICML 2023, July 2023 (Published) URL BibTeX
Empirical Inference Robust Machine Learning Conference Paper Provably Learning Object-Centric Representations Brady*, J., Zimmermann*, R. S., Sharma, Y., Schölkopf, B., von Kügelen, J., Brendel, W. Proceedings of the 40th International Conference on Machine Learning (ICML), 202:3038-3062, Proceedings of Machine Learning Research, (Editors: A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato and J. Scarlett), JMLR, Cambridge, MA, July 2023, *equal contribution (Published) URL BibTeX
Empirical Inference Robust Machine Learning Article Jacobian-based Causal Discovery with Nonlinear ICA Reizinger, P., Sharma, Y., Bethge, M., Schölkopf, B., Huszár, F., Brendel, W. Transactions on Machine Learning Research, April 2023 (Published) URL BibTeX