Kirill Bykov

According to our database, Kirill Bykov authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Do LLMs Experience an Internal Polylogue? Investigating Reasoning through the Lens of Personas.

Nils A. Herrmann, Leander Girrbach, Kirill Bykov, Zeynep Akata

CoRR, May, 2026

Explaining representations in deep neural networks.

Kirill Bykov

PhD thesis, 2026

2025

Deep Learning Meets Teleconnections: Improving S2S Predictions for European Winter Weather.

Philine Lou Bommer, Marlene Kretschmer, Fiona R. Spuler, Kirill Bykov, Marina M.-C. Höhne

CoRR, April, 2025

Explaining Bayesian Neural Networks.

Kirill Bykov, Marina M.-C. Höhne, Adelaida Creosteanu, Klaus-Robert Müller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft

Trans. Mach. Learn. Res., 2025

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework.

Laura Kopf, Nils Feldhus, Kirill Bykov, Philine Lou Bommer, Anna Hedström, Marina M.-C. Höhne, Oliver Eberle

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Manipulating Feature Visualizations with Gradient Slingshots.

Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Sebastian Lapuschkin, Kirill Bykov

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Manipulating Feature Visualizations with Gradient Slingshots.

Dilyara Bareeva, Marina M.-C. Höhne, Alexander Warnecke, Lukas Pirch, Klaus-Robert Müller, Konrad Rieck, Kirill Bykov

CoRR, 2024

CoSy: Evaluating Textual Explanations of Neurons.

Laura Kopf, Philine Lou Bommer, Anna Hedström, Sebastian Lapuschkin, Marina M.-C. Höhne, Kirill Bykov

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Visualizing the Diversity of Representations Learned by Bayesian Neural Networks.

Dennis Grinwald, Kirill Bykov, Shinichi Nakajima, Marina M.-C. Höhne

Trans. Mach. Learn. Res., 2023

DORA: Exploring Outlier Representations in Deep Neural Networks.

Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne

Trans. Mach. Learn. Res., 2023

Finding Spurious Correlations with Function-Semantic Contrast Analysis.

Kirill Bykov, Laura Kopf, Marina M.-C. Höhne

Proceedings of the Explainable Artificial Intelligence, 2023

Labeling Neural Representations with Inverse Recognition.

Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina M.-C. Höhne

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GPT3RecBot: a universal chatbot recommender of movies, books and music in Telegram.

Oleg Lashinin, Kirill Bykov, Marina Ananyeva, Sergey Kolesnikov

Proceedings of the Fifth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 17th ACM Conference on Recommender Systems (RecSys 2023), 2023

Mark My Words: Dangers of Watermarked Images in ImageNet.

Kirill Bykov, Klaus-Robert Müller, Marina M.-C. Höhne

Proceedings of the Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30, 2023

2022

DRAMSys4.0: An Open-Source Simulation Framework for In-depth DRAM Analyses.

Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn

Int. J. Parallel Program., 2022

NoiseGrad - Enhancing Explanations by Introducing Stochasticity to Model Weights.

Kirill Bykov, Anna Hedström, Shinichi Nakajima, Marina M.-C. Höhne

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2020

How Much Can I Trust You? - Quantifying Uncertainties in Explaining Neural Networks.

Kirill Bykov, Marina M.-C. Höhne, Klaus-Robert Müller, Shinichi Nakajima, Marius Kloft

CoRR, 2020

DRAMSys4.0: A Fast and Cycle-Accurate SystemC/TLM-Based DRAM Simulator.

Lukas Steiner, Matthias Jung, Felipe S. Prado, Kirill Bykov, Norbert Wehn

Proceedings of the Embedded Computer Systems: Architectures, Modeling, and Simulation, 2020