Locating multiple interacting quantitative trait loci using robust model selection. - Andreas Baierl; Andreas Futschik; Malgorzata Bogdan; Przemyslaw Biecek (Comput. Stat. Data Anal., 2007)

The role of intragenomic recombination rate in the evolution of population's genetic pool. - Marta Zawierta; Przemyslaw Biecek; Wojciech Waga; Stanislaw Cebrat (Theory Biosci., 2007)

Optimisation of Asymmetric Mutational Pressure and Selection Pressure Around the Universal Genetic Code. - Pawel Mackiewicz; Przemyslaw Biecek; Dorota Mackiewicz; Joanna Kiraga; Krystian Baczkowski; Maciej Sobczynski; Stanislaw Cebrat (ICCS (3), 2008)

Introducing Knowledge into Differential Expression Analysis. - Ewa Szczurek; Przemyslaw Biecek; Jerzy Tiuryn; Martin Vingron (J. Comput. Biol., 2010)

Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data. - Ewa Szczurek; Florian Markowetz; Irit Gat-Viks; Przemyslaw Biecek; Jerzy Tiuryn; Martin Vingron (BMC Bioinform., 2011)

Bi-Billboard: Symmetrization and Careful Choice of Informant Species Results in Higher Accuracy of Regulatory Element Prediction. - Norbert Dojer; Przemyslaw Biecek; Jerzy Tiuryn (J. Comput. Biol., 2011)

Merge and Select: Visualization of a likelihood based k-sample adaptive fusing and model selection. - Agnieszka Sitko; Przemyslaw Biecek (CoRR, 2017)

Retrieval and Analysis of Eurostat Open Data with the eurostat Package. - Leo Lahti; Janne Huovari; Markus Kainu; Przemyslaw Biecek (R J., 2017)

How much should you ask? On the question structure in QA systems. - Barbara Rychalska; Dominika Basaj; Anna Wróblewska; Przemyslaw Biecek (BlackboxNLP@EMNLP, 2018)

Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System. - Barbara Rychalska; Dominika Basaj; Anna Wróblewska; Przemyslaw Biecek (BlackboxNLP@EMNLP, 2018)

DALEX: explainers for complex predictive models. - Przemyslaw Biecek (CoRR, 2018)

auditor: an R Package for Model-Agnostic Visual Validation and Diagnostic. - Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2018)

Are you tough enough? Framework for Robustness Validation of Machine Comprehension Systems. - Barbara Rychalska; Dominika Basaj; Przemyslaw Biecek (CoRR, 2018)

DALEX: Explainers for Complex Predictive Models in R. - Przemyslaw Biecek (J. Mach. Learn. Res., 2018)

survxai: an R package for structure-agnostic explanations of survival models. - Aleksandra Grudziaz; Alicja Gosiewska; Przemyslaw Biecek (J. Open Source Softw., 2018)

Explanations of Model Predictions with live and breakDown Packages. - Mateusz Staniak; Przemyslaw Biecek (R J., 2018)

Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer. - Katarzyna Kobylinska; Tomasz Mikolajczyk; Mariusz Adamek; Tadeusz Orlowski; Przemyslaw Biecek (KR4HC/ProHealth/TEAAM@AIME, 2019)

Named Entity Recognition - Is There a Glass Ceiling? - Tomasz Stanislawek; Anna Wróblewska; Alicja Wójcicka; Daniel Ziembicki; Przemyslaw Biecek (CoNLL, 2019)

Models in the Wild: On Corruption Robustness of Neural NLP Systems. - Barbara Rychalska; Dominika Basaj; Alicja Gosiewska; Przemyslaw Biecek (ICONIP (3), 2019)

SAFE ML: Surrogate Assisted Feature Extraction for Model Learning. - Alicja Gosiewska; Aleksandra Gacek; Piotr Lubon; Przemyslaw Biecek (CoRR, 2019)

iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models. - Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2019)

Clustering of Medical Free-Text Records Based on Word Embeddings. - Adam Gabriel Dobrakowski; Agnieszka Mykowiecka 001; Malgorzata Marciniak; Wojciech Jaworski; Przemyslaw Biecek (CoRR, 2019)

Model Development Process. - Przemyslaw Biecek (CoRR, 2019)

EPP: interpretable score of model predictive power. - Alicja Gosiewska; Mateusz Bakala; Katarzyna Woznica; Maciej Zwolinski; Przemyslaw Biecek (CoRR, 2019)

modelStudio: Interactive Studio with Explanations for ML Predictive Models. - Hubert Baniecki; Przemyslaw Biecek (J. Open Source Softw., 2019)

pyCeterisParibus: explaining Machine Learning models with Ceteris Paribus Profiles in Python. - Michal Kuzba; Ewa Baranowska; Przemyslaw Biecek (J. Open Source Softw., 2019)

modelDown: automated website generator with interpretable documentation for predictive machine learning models. - Kamil Romaszko; Magda Tatarynowicz; Mateusz Urbanski; Przemyslaw Biecek (J. Open Source Softw., 2019)

auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics. - Alicja Gosiewska; Przemyslaw Biecek (R J., 2019)

The Landscape of R Packages for Automated Exploratory Data Analysis. - Mateusz Staniak; Przemyslaw Biecek (R J., 2019)

Explainable AI Methods - A Brief Overview. - Andreas Holzinger; Anna Saranti; Christoph Molnar; Przemyslaw Biecek; Wojciech Samek (xxAI@ICML, 2020)

What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations. - Michal Kuzba; Przemyslaw Biecek (PKDD/ECML Workshops, 2020)

KRAB ZNF explorer - the online tool for the exploration of the transcriptomic profiles of KRAB-ZNF factors in The Cancer Genome Atlas. - Rafal Cylwa; Kornel Kielczewski; Marta Machnik; Urszula Oleksiewicz; Przemyslaw Biecek (Bioinform., 2020)

Lifting Interpretability-Performance Trade-off via Automated Feature Engineering. - Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2020)

Towards better understanding of meta-features contributions. - Katarzyna Woznica; Przemyslaw Biecek (CoRR, 2020)

Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout. - Filip Gralinski; Tomasz Stanislawek; Anna Wróblewska; Dawid Lipinski; Agnieszka Kaliska; Paulina Rosalska; Bartosz Topolski; Przemyslaw Biecek (CoRR, 2020)

The Grammar of Interactive Explanatory Model Analysis. - Hubert Baniecki; Przemyslaw Biecek (CoRR, 2020)

Interpretable Meta-Measure for Model Performance. - Alicja Gosiewska; Katarzyna Woznica; Przemyslaw Biecek (CoRR, 2020)

Does imputation matter? Benchmark for predictive models. - Katarzyna Woznica; Przemyslaw Biecek (CoRR, 2020)

MementoML: Performance of selected machine learning algorithm configurations on OpenML100 datasets. - Wojciech Kretowicz; Przemyslaw Biecek (CoRR, 2020)

Landscape of R packages for eXplainable Artificial Intelligence. - Szymon Maksymiuk; Alicja Gosiewska; Przemyslaw Biecek (CoRR, 2020)

Do not repeat these mistakes - a critical appraisal of applications of explainable artificial intelligence for image based COVID-19 detection. - Weronika Hryniewska; Przemyslaw Bombinski; Patryk Szatkowski; Paulina Tomaszewska; Artur Przelaskowski; Przemyslaw Biecek (CoRR, 2020)

Responsible Prediction Making of COVID-19 Mortality (Student Abstract). - Hubert Baniecki; Przemyslaw Biecek (AAAI, 2021)

Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts. - Tomasz Stanislawek; Filip Gralinski; Anna Wróblewska; Dawid Lipinski; Agnieszka Kaliska; Paulina Rosalska; Bartosz Topolski; Przemyslaw Biecek (ICDAR (1), 2021)

Cleora: A Simple, Strong and Scalable Graph Embedding Scheme. - Barbara Rychalska; Piotr Babel; Konrad Goluchowski; Andrzej Michalowski; Jacek Dabrowski 004; Przemyslaw Biecek (ICONIP (4), 2021)

Supporting Doctor's Decisions Based on Electronic Medical Documentation in Polish. - Wojciech Jaworski; Przemyslaw Biecek; Adam Gabriel Dobrakowski; Malgorzata Marciniak; Agnieszka Mykowiecka 001; Agnieszka Morusiewicz; Joanna Przetacka; Lukasz Kaminski (MedInfo, 2021)

Towards Explainable Meta-learning. - Katarzyna Woznica; Przemyslaw Biecek (PKDD/ECML Workshops (1), 2021)

fairmodels: A Flexible Tool For Bias Detection, Visualization, And Mitigation. - Jakub Wisniewski; Przemyslaw Biecek (CoRR, 2021)

Triplot: model agnostic measures and visualisations for variable importance in predictive models that take into account the hierarchical correlation structure. - Katarzyna Pekala; Katarzyna Woznica; Przemyslaw Biecek (CoRR, 2021)

Enabling Machine Learning Algorithms for Credit Scoring - Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models. - Przemyslaw Biecek; Marcin Chlebus; Janusz Gajda; Alicja Gosiewska; Anna Kozak; Dominik Ogonowski; Jakub Sztachelski; Piotr Wojewnik (CoRR, 2021)

Do not explain without context: addressing the blind spot of model explanations. - Katarzyna Woznica; Katarzyna Pekala; Hubert Baniecki; Wojciech Kretowicz; Elzbieta Sienkiewicz; Przemyslaw Biecek (CoRR, 2021)

MAIR: Framework for mining relationships between research articles, strategies, and regulations in the field of explainable artificial intelligence. - Stanislaw Gizinski; Michal Kuzba; Bartosz Pielinski; Julian Sienkiewicz; Stanislaw Laniewski; Przemyslaw Biecek (CoRR, 2021)

Simpler is better: Lifting interpretability-performance trade-off via automated feature engineering. - Alicja Gosiewska; Anna Kozak; Przemyslaw Biecek (Decis. Support Syst., 2021)

Interpretable segmentation of medical free-text records based on word embeddings. - Adam Gabriel Dobrakowski; Agnieszka Mykowiecka 001; Malgorzata Marciniak; Wojciech Jaworski; Przemyslaw Biecek (J. Intell. Inf. Syst., 2021)

dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python. - Hubert Baniecki; Wojciech Kretowicz; Piotr Piatyszek; Jakub Wisniewski; Przemyslaw Biecek (J. Mach. Learn. Res., 2021)

Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies. - Weronika Hryniewska; Przemyslaw Bombinski; Patryk Szatkowski; Paulina Tomaszewska; Artur Przelaskowski; Przemyslaw Biecek (Pattern Recognit., 2021)

Manipulating SHAP via Adversarial Data Perturbations (Student Abstract). - Hubert Baniecki; Przemyslaw Biecek (AAAI, 2022)

Explainable expected goal models for performance analysis in football analytics. - Mustafa Cavus; Przemyslaw Biecek (DSAA, 2022)

Interpretable Meta-Score for Model Performance: Extended Abstract. - Alicja Gosiewska; Katarzyna Woznica; Przemyslaw Biecek (Meta-Knowledge Transfer @ ECML/PKDD, 2022)

Fooling Partial Dependence via Data Poisoning. - Hubert Baniecki; Wojciech Kretowicz; Przemyslaw Biecek (ECML/PKDD (3), 2022)

A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer's Disease. - Angela Lombardi; Domenico Diacono; Nicola Amoroso; Przemyslaw Biecek; Alfonso Monaco; Loredana Bellantuono; Ester Pantaleo; Giancarlo Logroscino; Roberto De Blasi; Sabina Tangaro; Roberto Bellotti (Brain Informatics, 2022)

Consolidated learning - a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV. - Katarzyna Woznica; Mateusz Grzyb; Zuzanna Trafas; Przemyslaw Biecek (CoRR, 2022)

Performance, Opaqueness, Consequences, and Assumptions: Simple questions for responsible planning of machine learning solutions. - Przemyslaw Biecek (CoRR, 2022)

Climate Policy Tracker: Pipeline for automated analysis of public climate policies. - Artur Zólkowski; Mateusz Krzyzinski; Piotr Wilczynski; Stanislaw Gizinski; Emilia Wisnios; Bartosz Pielinski; Julian Sienkiewicz; Przemyslaw Biecek (CoRR, 2022)

Transparency, auditability, and explainability of machine learning models in credit scoring. - Michael Bücker; Gero Szepannek; Alicja Gosiewska; Przemyslaw Biecek (J. Oper. Res. Soc., 2022)

fairmodels: a Flexible Tool for Bias Detection, Visualization, and Mitigation in Binary Classification Models. - Jakub Wisniewski; Przemyslaw Biecek (R J., 2022)

Interpretable meta-score for model performance. - Alicja Gosiewska; Katarzyna Woznica; Przemyslaw Biecek (Nat. Mac. Intell., 2022)

Hospital Length of Stay Prediction Based on Multi-modal Data Towards Trustworthy Human-AI Collaboration in Radiomics. - Hubert Baniecki; Bartlomiej Sobieski; Przemyslaw Bombinski; Patryk Szatkowski; Przemyslaw Biecek (AIME, 2023)

Towards Evaluating Explanations of Vision Transformers for Medical Imaging. - Piotr Komorowski; Hubert Baniecki; Przemyslaw Biecek (CVPR Workshops, 2023)

The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems. - Adrian Stando; Mustafa Cavus; Przemyslaw Biecek (LIDTA, 2023)

HADES: Homologous Automated Document Exploration and Summarization. - Piotr Wilczynski; Artur Zólkowski; Mateusz Krzyzinski; Emilia Wisnios; Bartosz Pielinski; Stanislaw Gizinski; Julian Sienkiewicz; Przemyslaw Biecek (CoRR, 2023)

Performance is not enough: a story of the Rashomon's quartet. - Przemyslaw Biecek; Hubert Baniecki; Mateusz Krzyzinski (CoRR, 2023)

Challenges facing the explainability of age prediction models: case study for two modalities. - Mikolaj Spytek; Weronika Hryniewska-Guzik; Jaroslaw Zygierewicz; Jacek Rogala; Przemyslaw Biecek (CoRR, 2023)

Prevention is better than cure: a case study of the abnormalities detection in the chest. - Weronika Hryniewska; Piotr Czarnecki; Jakub Wisniewski; Przemyslaw Bombinski; Przemyslaw Biecek (CoRR, 2023)

SeFNet: Bridging Tabular Datasets with Semantic Feature Nets. - Katarzyna Woznica; Piotr Wilczynski; Przemyslaw Biecek (CoRR, 2023)

Explainable AI with counterfactual paths. - Bastian Pfeifer; Mateusz Krzyzinski; Hubert Baniecki; Anna Saranti; Andreas Holzinger; Przemyslaw Biecek (CoRR, 2023)

Multi-task learning for classification, segmentation, reconstruction, and detection on chest CT scans. - Weronika Hryniewska-Guzik; Maria Kedzierska; Przemyslaw Biecek (CoRR, 2023)

Exploration of Rashomon Set Assists Explanations for Medical Data. - Katarzyna Kobylinska; Mateusz Krzyzinski; Rafal Machowicz; Mariusz Adamek; Przemyslaw Biecek (CoRR, 2023)

Glocal Explanations of Expected Goal Models in Soccer. - Mustafa Cavus; Adrian Stando; Przemyslaw Biecek (CoRR, 2023)

Be Careful When Evaluating Explanations Regarding Ground Truth. - Hubert Baniecki; Maciej Chrabaszcz; Andreas Holzinger; Bastian Pfeifer; Anna Saranti; Przemyslaw Biecek (CoRR, 2023)

SurvSHAP(t): Time-dependent explanations of machine learning survival models. - Mateusz Krzyzinski; Mikolaj Spytek; Hubert Baniecki; Przemyslaw Biecek (Knowl. Based Syst., 2023)

survex: an R package for explaining machine learning survival models. - Mikolaj Spytek; Mateusz Krzyzinski; Sophie Hanna Langbein; Hubert Baniecki; Marvin N. Wright; Przemyslaw Biecek (Bioinform., 2023)

Generative AI models should include detection mechanisms as a condition for public release. - Alistair Knott; Dino Pedreschi; Raja Chatila 001; Tapabrata Chakraborti; Susan Leavy; Ricardo Baeza-Yates; David M. Eyers; Andrew Trotman; Paul D. Teal; Przemyslaw Biecek; Stuart Russell 001; Yoshua Bengio (Ethics Inf. Technol., 2023)

Red-Teaming Segment Anything Model. - Krzysztof Jankowski; Bartlomiej Sobieski; Mateusz Kwiatkowski; Jakub Szulc; Michal Janik; Hubert Baniecki; Przemyslaw Biecek (CVPR Workshops, 2024)

Resistance Against Manipulative AI: Key Factors and Possible Actions. - Piotr Wilczynski; Wiktoria Mieleszczenko-Kowszewicz; Przemyslaw Biecek (ECAI, 2024)

Global Counterfactual Directions. - Bartlomiej Sobieski; Przemyslaw Biecek (ECCV (63), 2024)

Position: Explain to Question not to Justify. - Przemyslaw Biecek; Wojciech Samek (ICML, 2024)

Position: Do Not Explain Vision Models Without Context. - Paulina Tomaszewska; Przemyslaw Biecek (ICML, 2024)

Swin SMT: Global Sequential Modeling for Enhancing 3D Medical Image Segmentation. - Szymon Plotka; Maciej Chrabaszcz; Przemyslaw Biecek (MICCAI (8), 2024)

On the Robustness of Global Feature Effect Explanations. - Hubert Baniecki; Giuseppe Casalicchio; Bernd Bischl; Przemyslaw Biecek (ECML/PKDD (2), 2024)

Towards a crowdsourced framework for online hate speech moderation - a case study in the Indian political scenario. - Avigyan Bhattacharya; Tapabrata Chakraborti; Subhadip Basu; Alistair Knott; Dino Pedreschi; Raja G. Chatila; Susan Leavy; David M. Eyers; Paul D. Teal; Przemyslaw Biecek (WebSci (Companion), 2024)

SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps. - Oleksandr Davydko; Vladimir Pavlov; Przemyslaw Biecek; Luca Longo (xAI (4), 2024)

CNN-Based Explanation Ensembling for Dataset, Representation and Explanations Evaluation. - Weronika Hryniewska-Guzik; Luca Longo; Przemyslaw Biecek (xAI (2), 2024)

Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data. - André Fonseca; Mikolaj Spytek; Przemyslaw Biecek; Clara Cordeiro; Nuno Sepúlveda (BioData Min., 2024)

Deep spatial context: when attention-based models meet spatial regression. - Paulina Tomaszewska; Elzbieta Sienkiewicz; Mai P. Hoang; Przemyslaw Biecek (CoRR, 2024)

NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques. - Weronika Hryniewska-Guzik; Bartosz Sawicki; Przemyslaw Biecek (CoRR, 2024)

Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography. - Przemyslaw Bombinski; Patryk Szatkowski; Bartlomiej Sobieski; Tymoteusz Kwiecinski; Szymon Plotka; Mariusz Adamek; Marcin Banasiuk; Mariusz I. Furmanek; Przemyslaw Biecek (CoRR, 2024)

Explain to Question not to Justify. - Przemyslaw Biecek; Wojciech Samek (CoRR, 2024)

Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI. - Vladimir Zaigrajew; Hubert Baniecki; Lukasz Tulczyjew; Agata M. Wijata; Jakub Nalepa; Nicolas Longépé; Przemyslaw Biecek (CoRR, 2024)

Interpretable Machine Learning for Survival Analysis. - Sophie Hanna Langbein; Mateusz Krzyzinski; Mikolaj Spytek; Hubert Baniecki; Przemyslaw Biecek; Marvin N. Wright (CoRR, 2024)

A comparative analysis of deep learning models for lung segmentation on X-ray images. - Weronika Hryniewska-Guzik; Jakub Bilski; Bartosz Chrostowski; Jakub Drak Sbahi; Przemyslaw Biecek (CoRR, 2024)

Position paper: Do not explain (vision models) without context. - Paulina Tomaszewska; Przemyslaw Biecek (CoRR, 2024)

An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification. - Mustafa Cavus; Przemyslaw Biecek (CoRR, 2024)

Does context matter in digital pathology? - Paulina Tomaszewska; Mateusz Sperkowski; Przemyslaw Biecek (CoRR, 2024)

Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation. - Szymon Plotka; Maciej Chrabaszcz; Przemyslaw Biecek (CoRR, 2024)

The Dark Patterns of Personalized Persuasion in Large Language Models: Exposing Persuasive Linguistic Features for Big Five Personality Traits in LLMs Responses. - Wiktoria Mieleszczenko-Kowszewicz; Dawid Pludowski; Filip Kolodziejczyk; Jakub Swistak; Julian Sienkiewicz; Przemyslaw Biecek (CoRR, 2024)

Adversarial attacks and defenses in explainable artificial intelligence: A survey. - Hubert Baniecki; Przemyslaw Biecek (Inf. Fusion, 2024)

Performance Is Not Enough: The Story Told by a Rashomon Quartet. - Przemyslaw Biecek; Hubert Baniecki; Mateusz Krzyzinski; Dianne Cook (J. Comput. Graph. Stat., 2024)

Big Tech influence over AI research revisited: Memetic analysis of attribution of ideas to affiliation. - Stanislaw Gizinski; Paulina Kaczynska; Hubert Ruczynski; Emilia Wisnios; Bartosz Pielinski; Przemyslaw Biecek; Julian Sienkiewicz (J. Informetrics, 2024)

LIMEcraft: handcrafted superpixel selection and inspection for Visual eXplanations. - Weronika Hryniewska; Adrianna Grudzien; Przemyslaw Biecek (Mach. Learn., 2024)

Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks. - Katarzyna Woznica; Mateusz Grzyb; Zuzanna Trafas; Przemyslaw Biecek (Mach. Learn., 2024)

The grammar of interactive explanatory model analysis. - Hubert Baniecki; Dariusz Parzych; Przemyslaw Biecek (Data Min. Knowl. Discov., 2024)

Exploration of the Rashomon Set Assists Trustworthy Explanations for Medical Data. - Katarzyna Kobylinska; Mateusz Krzyzinski; Rafal Machowicz; Mariusz Adamek; Przemyslaw Biecek (IEEE J. Biomed. Health Informatics, 2024)

AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Deep Spatial Context: When Attention-Based Models Meet Spatial Regression (Digital Pathology). - Paulina Tomaszewska; Elzbieta Sienkiewicz; Mai P. Hoang; Przemyslaw Biecek (AIME (1), 2025)

Efficient and Accurate Explanation Estimation with Distribution Compression. - Hubert Baniecki; Giuseppe Casalicchio; Bernd Bischl; Przemyslaw Biecek (ICLR, 2025)

Rethinking Visual Counterfactual Explanations Through Region Constraint. - Bartlomiej Sobieski; Jakub Grzywaczewski; Bartlomiej Sadlej; Matthew Tivnan; Przemyslaw Biecek (ICLR, 2025)

Aggregated Attributions for Explanatory Analysis of 3D Segmentation Models. - Maciej Chrabaszcz; Hubert Baniecki; Piotr Komorowski; Szymon Plotka; Przemyslaw Biecek (WACV, 2025)

Interpretable machine learning for time-to-event prediction in medicine and healthcare. - Hubert Baniecki; Bartlomiej Sobieski; Patryk Szatkowski; Przemyslaw Bombinski; Przemyslaw Biecek (Artif. Intell. Medicine, 2025)

Investigating the impact of balancing, filtering, and complexity on predictive multiplicity: A data-centric perspective. - Mustafa Cavus; Przemyslaw Biecek (Inf. Fusion, 2025)

Mind What You Ask For: Emotional and Rational Faces of Persuasion by Large Language Models. - Wiktoria Mieleszczenko-Kowszewicz; Beata Bajcar; Jolanta Babiak; Berenika Dyczek; Jakub Swistak; Przemyslaw Biecek (CoRR, 2025)

Interpreting CLIP with Hierarchical Sparse Autoencoders. - Vladimir Zaigrajew; Hubert Baniecki; Przemyslaw Biecek (CoRR, 2025)

Exploring local explanations of nonlinear models using animated linear projections. - Nicholas Spyrison; Dianne Cook; Przemyslaw Biecek (Comput. Stat., 2025)

Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning. - Hubert Baniecki; Przemyslaw Biecek (CoRR, 2025)

The Role of Hyperparameters in Predictive Multiplicity. - Mustafa Cavus; Katarzyna Woznica; Przemyslaw Biecek (CoRR, 2025)

MASCOTS: Model-Agnostic Symbolic COunterfactual explanations for Time Series. - Dawid Pludowski; Francesco Spinnato; Piotr Wilczynski; Krzysztof Kotowski; Evridiki Vasileia Ntagiou; Riccardo Guidotti; Przemyslaw Biecek (CoRR, 2025)

Trojan Horse Hunt in Time Series Forecasting for Space Operations. - Krzysztof Kotowski; Ramez Shendy; Jakub Nalepa; Przemyslaw Biecek; Piotr Wilczynski; Agata Kaczmarek; Dawid Pludowski; Artur Janicki; Evridiki Vasileia Ntagiou (CoRR, 2025)

System-Embedded Diffusion Bridge Models. - Bartlomiej Sobieski; Matthew Tivnan; Yuang Wang; Siyeop Yoon; Pengfei Jin; Dufan Wu; Quanzheng Li; Przemyslaw Biecek (CoRR, 2025)

X-ray transferable polyrepresentation learning. - Weronika Hryniewska-Guzik; Przemyslaw Biecek (CoRR, 2025)

Fake or Real: The Impostor Hunt in Texts for Space Operations. - Agata Kaczmarek; Dawid Pludowski; Piotr Wilczynski; Krzysztof Kotowski; Ramez Shendy; Evridiki Vasileia Ntagiou; Jakub Nalepa; Artur Janicki; Przemyslaw Biecek (CoRR, 2025)

Beyond the Single-Best Model: Rashomon Partial Dependence Profile for Trustworthy Explanations in AutoML. - Mustafa Cavus; Jan N. van Rijn; Przemyslaw Biecek (CoRR, 2025)

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions. - Hubert Baniecki; Maximilian Muschalik; Fabian Fumagalli; Barbara Hammer; Eyke Hüllermeier; Przemyslaw Biecek (CoRR, 2025)

Explaining and visualizing black-box models through counterfactual paths. - Bastian Pfeifer; Mateusz Krzyzinski; Hubert Baniecki; Andreas Holzinger; Przemyslaw Biecek (Pattern Anal. Appl., 2025)

SeFNet: Linking tabular datasets with semantic feature nets. - Katarzyna Woznica; Piotr Wilczynski; Przemyslaw Biecek (Inf. Fusion, 2026)