Bartlomiej Twardowski

81 papers A* 12A 6Misc 1Journal 47Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cross-Modal Prototype Alignment and Mixing for Training-Free Few-Shot Classification. CoRR Dipam Goswami, Simone Magistri, Gido M. van de Ven, Bartlomiej Twardowski, Andrew D. Bagdanov, Tinne Tuytelaars, Joost van de Weijer
2026	J	`jnl`	IsoCLIP: Decomposing CLIP Projectors for Efficient Intra-modal Alignment. CoRR Simone Magistri, Dipam Goswami, Marco Mistretta, Bartlomiej Twardowski, Joost van de Weijer, Andrew D. Bagdanov
2026	—	`conf`	Realistic Evaluation of Test-Time Adaptation: Unsupervised Model Selection. VISAPP (1) Sebastian Cygert, Damian Sójka, Tomasz Trzcinski, Bartlomiej Twardowski
2025	J	`jnl`	Accurate and Efficient Low-Rank Model Merging in Core Space. CoRR Aniello Panariello, Daniel Marczak, Simone Magistri, Angelo Porrello, Bartlomiej Twardowski, Andrew D. Bagdanov, Simone Calderara, Joost van de Weijer
2025	J	`jnl`	Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual Learning. CoRR Stanislaw Pawlak, Bartlomiej Twardowski, Tomasz Trzcinski, Joost van de Weijer
2025	J	`jnl`	Backdoor Vectors: a Task Arithmetic View on Backdoor Attacks and Defenses. CoRR Stanislaw Pawlak, Jan Dubinski, Daniel Marczak, Bartlomiej Twardowski
2025	A	`conf`	GUIDE: Guidance-Based Incremental Learning with Diffusion Models. ECAI Bartosz Cywinski, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski, Lukasz Kucinski
2025	A*	`conf`	Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers. ICML Filip Szatkowski, Yaoyue Zheng, Fei Yang, Tomasz Trzcinski, Bartlomiej Twardowski, Joost van de Weijer
2025	A*	`conf`	No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces. ICML Daniel Marczak, Simone Magistri, Sebastian Cygert, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
2025	J	`jnl`	No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces. CoRR Daniel Marczak, Simone Magistri, Sebastian Cygert, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
2025	J	`jnl`	Query Drift Compensation: Enabling Compatibility in Continual Learning of Retrieval Embedding Models. CoRR Dipam Goswami, Liying Wang, Bartlomiej Twardowski, Joost van de Weijer
2025	A*	`conf`	The Art of Deception: Color Visual Illusions and Diffusion Models. CVPR Alexandra Gomez-Villa, Kai Wang, C. Alejandro Párraga, Bartlomiej Twardowski, Jesus Malo, Javier Vazquez-Corral, Joost van de Weijer
2024	A	`conf`	AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. BMVC Damian Sójka, Bartlomiej Twardowski, Tomasz Trzcinski, Sebastian Cygert
2024	J	`jnl`	Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning. CoRR Filip Szatkowski, Fei Yang, Bartlomiej Twardowski, Tomasz Trzcinski, Joost van de Weijer
2024	A	`conf`	Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. WACV Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
2024	J	`jnl`	Augmentation-aware self-supervised learning with conditioned projector. Knowl. Based Syst. Marcin Przewiezlikowski, Mateusz Pyla, Bartosz Zielinski, Bartlomiej Twardowski, Jacek Tabor, Marek Smieja
2024	—	`conf`	Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers. CVPR Workshops Dipam Goswami, Bartlomiej Twardowski, Joost van de Weijer
2024	J	`jnl`	Calibrating Higher-Order Statistics for Few-Shot Class-Incremental Learning with Pre-trained Vision Transformers. CoRR Dipam Goswami, Bartlomiej Twardowski, Joost van de Weijer
2024	—	`conf`	Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery. ECCV (11) Grzegorz Rypesc, Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
2024	J	`jnl`	Covariances for Free: Exploiting Mean Distributions for Federated Learning with Pre-Trained Models. CoRR Dipam Goswami, Simone Magistri, Kai Wang, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
2024	A*	`conf`	Divide and not forget: Ensemble of selectively trained experts in Continual Learning. ICLR Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski
2024	J	`jnl`	Divide and not forget: Ensemble of selectively trained experts in Continual Learning. CoRR Grzegorz Rypesc, Sebastian Cygert, Valeriya Khan, Tomasz Trzcinski, Bartosz Zielinski, Bartlomiej Twardowski
2024	—	`conf`	Exemplar-Free Continual Representation Learning via Learnable Drift Compensation. ECCV (7) Alex Gomez-Villa, Dipam Goswami, Kai Wang, Andrew D. Bagdanov, Bartlomiej Twardowski, Joost van de Weijer
2024	J	`jnl`	Exemplar-free Continual Representation Learning via Learnable Drift Compensation. CoRR Alex Gomez-Villa, Dipam Goswami, Kai Wang, Andrew D. Bagdanov, Bartlomiej Twardowski, Joost van de Weijer
2024	J	`jnl`	GUIDE: Guidance-based Incremental Learning with Diffusion Models. CoRR Bartosz Cywinski, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski, Lukasz Kucinski
2024	J	`jnl`	Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. IEEE Access Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski
2024	—	`conf`	MAGMAX: Leveraging Model Merging for Seamless Continual Learning. ECCV (85) Daniel Marczak, Bartlomiej Twardowski, Tomasz Trzcinski, Sebastian Cygert
2024	J	`jnl`	MagMax: Leveraging Model Merging for Seamless Continual Learning. CoRR Daniel Marczak, Bartlomiej Twardowski, Tomasz Trzcinski, Sebastian Cygert
2024	A	`conf`	Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. WACV Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer
2024	J	`jnl`	Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection. CoRR Sebastian Cygert, Damian Sójka, Tomasz Trzcinski, Bartlomiej Twardowski
2024	A*	`conf`	Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. CVPR Dipam Goswami, Albin Soutif-Cormerais, Yuyang Liu, Sandesh Kamath, Bartlomiej Twardowski, Joost van de Weijer
2024	J	`jnl`	Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. CoRR Dipam Goswami, Albin Soutif-Cormerais, Yuyang Liu, Sandesh Kamath, Bartlomiej Twardowski, Joost van de Weijer
2024	—	`conf`	Revisiting Supervision for Continual Representation Learning. ECCV (6) Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
2024	A*	`conf`	Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. NeurIPS Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
2024	J	`jnl`	Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. CoRR Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
2024	J	`jnl`	The Art of Deception: Color Visual Illusions and Diffusion Models. CoRR Alex Gomez-Villa, Kai Wang, C. Alejandro Párraga, Bartlomiej Twardowski, Jesus Malo, Javier Vazquez-Corral, Joost van de Weijer
2024	A	`conf`	Zero-Waste Machine Learning. ECAI Tomasz Trzcinski, Bartlomiej Twardowski, Bartosz Zielinski, Kamil Adamczewski, Bartosz Wójcik
2023	—	`conf`	AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. ICCV (Workshops) Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
2023	J	`jnl`	AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. CoRR Damian Sójka, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
2023	—	`conf`	Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. ICCV (Workshops) Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
2023	J	`jnl`	Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. CoRR Filip Szatkowski, Mateusz Pyla, Marcin Przewiezlikowski, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
2023	J	`jnl`	Augmentation-aware Self-supervised Learning with Guided Projector. CoRR Marcin Przewiezlikowski, Mateusz Pyla, Bartosz Zielinski, Bartlomiej Twardowski, Jacek Tabor, Marek Smieja
2023	J	`jnl`	Bayesian Flow Networks in Continual Learning. CoRR Mateusz Pyla, Kamil Deja, Bartlomiej Twardowski, Tomasz Trzcinski
2023	J	`jnl`	Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. IEEE Trans. Pattern Anal. Mach. Intell. Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer
2023	J	`jnl`	Exploiting Graph Structured Cross-Domain Representation for Multi-Domain Recommendation. CoRR Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya
2023	—	`conf`	Exploiting Graph Structured Cross-Domain Representation for Multi-domain Recommendation. ECIR (1) Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya
2023	A*	`conf`	FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. NeurIPS Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer
2023	J	`jnl`	FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning. CoRR Dipam Goswami, Yuyang Liu, Bartlomiej Twardowski, Joost van de Weijer
2023	J	`jnl`	FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems. CoRR Francesco Fabbri, Xianghang Liu, Jack R. McKenzie, Bartlomiej Twardowski, Tri Kurniawan Wijaya
2023	J	`jnl`	Generalized Continual Category Discovery. CoRR Daniel Marczak, Grzegorz Rypesc, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
2023	A*	`conf`	ICICLE: Interpretable Class Incremental Continual Learning. ICCV Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski
2023	J	`jnl`	ICICLE: Interpretable Class Incremental Continual Learning. CoRR Dawid Rymarczyk, Joost van de Weijer, Bartosz Zielinski, Bartlomiej Twardowski
2023	—	`conf`	Looking through the past: better knowledge retention for generative replay in continual learning. ICCV (Workshops) Valeriya Khan, Sebastian Cygert, Bartlomiej Twardowski, Tomasz Trzcinski
2023	J	`jnl`	Looking through the past: better knowledge retention for generative replay in continual learning. CoRR Valeriya Khan, Sebastian Cygert, Kamil Deja, Tomasz Trzcinski, Bartlomiej Twardowski
2023	J	`jnl`	MM-GEF: Multi-modal representation meet collaborative filtering. CoRR Hao Wu, Alejandro Ariza-Casabona, Bartlomiej Twardowski, Tri Kurniawan Wijaya
2023	A*	`conf`	Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training. ICLR Simone Zini, Alex Gomez-Villa, Marco Buzzelli, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
2023	J	`jnl`	Plasticity-Optimized Complementary Networks for Unsupervised Continual Learning. CoRR Alex Gomez-Villa, Bartlomiej Twardowski, Kai Wang, Joost van de Weijer
2023	J	`jnl`	Revisiting Supervision for Continual Representation Learning. CoRR Daniel Marczak, Sebastian Cygert, Tomasz Trzcinski, Bartlomiej Twardowski
2023	J	`jnl`	Technical Report for ICCV 2023 Visual Continual Learning Challenge: Continuous Test-time Adaptation for Semantic Segmentation. CoRR Damian Sójka, Yuyang Liu, Dipam Goswami, Sebastian Cygert, Bartlomiej Twardowski, Joost van de Weijer
2022	—	`conf`	Continually Learning Self-Supervised Representations with Projected Functional Regularization. CVPR Workshops Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer
2022	J	`jnl`	Online Meta-Learning for Model Update Aggregation in Federated Learning for Click-Through Rate Prediction. CoRR Xianghang Liu, Bartlomiej Twardowski, Tri Kurniawan Wijaya
2022	J	`jnl`	Planckian jitter: enhancing the color quality of self-supervised visual representations. CoRR Simone Zini, Marco Buzzelli, Bartlomiej Twardowski, Joost van de Weijer
2021	J	`jnl`	Continually Learning Self-Supervised Representations with Projected Functional Regularization. CoRR Alex Gomez-Villa, Bartlomiej Twardowski, Lu Yu, Andrew D. Bagdanov, Joost van de Weijer
2021	—	`conf`	Metric Learning for Session-Based Recommendations. ECIR (1) Bartlomiej Twardowski, Pawel Zawistowski, Szymon Zaborowski
2021	J	`jnl`	Metric Learning for Session-based Recommendations. CoRR Bartlomiej Twardowski, Pawel Zawistowski, Szymon Zaborowski
2021	J	`jnl`	On the importance of cross-task features for class-incremental learning. CoRR Albin Soutif-Cormerais, Marc Masana, Joost van de Weijer, Bartlomiej Twardowski
2021	—	`conf`	Reducing Label Effort: Self-Supervised meets Active Learning. ICCVW Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan Raducanu
2021	J	`jnl`	Reducing Label Effort: Self-Supervised meets Active Learning. CoRR Javad Zolfaghari Bengar, Joost van de Weijer, Bartlomiej Twardowski, Bogdan Raducanu
2020	J	`jnl`	Class-incremental learning: survey and performance evaluation. CoRR Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer
2020	J	`jnl`	On Class Orderings for Incremental Learning. CoRR Marc Masana, Bartlomiej Twardowski, Joost van de Weijer
2020	A*	`conf`	Orderless Recurrent Models for Multi-Label Classification. CVPR Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer
2020	A*	`conf`	RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. NeurIPS Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
2020	J	`jnl`	RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. CoRR Riccardo Del Chiaro, Bartlomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer
2020	A*	`conf`	Semantic Drift Compensation for Class-Incremental Learning. CVPR Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer
2020	J	`jnl`	Semantic Drift Compensation for Class-Incremental Learning. CoRR Lu Yu, Bartlomiej Twardowski, Xialei Liu, Luis Herranz, Kai Wang, Yongmei Cheng, Shangling Jui, Joost van de Weijer
2019	J	`jnl`	Deep Learning Optimization Tasks and Metaheuristic Methods. Fundam. Informaticae Rafal Biedrzycki, Pawel Zawistowski, Bartlomiej Twardowski
2019	J	`jnl`	Orderless Recurrent Models for Multi-label Classification. CoRR Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa, Bartlomiej Twardowski, Joost van de Weijer
2016	A	`conf`	Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks. RecSys Bartlomiej Twardowski
2015	—	`conf`	IoT and Context-Aware Mobile Recommendations Using Multi-agent Systems. WI-IAT (1) Bartlomiej Twardowski, Dominik Ryzko
2014	—	`conf`	Multi-agent Architecture for Real-Time Big Data Processing. WI-IAT (3) Bartlomiej Twardowski, Dominik Ryzko
2012	Misc	`conf`	Domain Dependent Product Feature and Opinion Extraction Based on E-Commerce Websites. MISSI Bartlomiej Twardowski, Piotr Gawrysiak