The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data. - Mateusz Lango; Jerzy Stefanowski (NFMCP, 2015)

Diversity Analysis on Imbalanced Data Using Neighbourhood and Roughly Balanced Bagging Ensembles. - Jerzy Blaszczynski; Mateusz Lango (ICAISC (1), 2016)

PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis. - Mateusz Lango; Dariusz Brzezinski; Jerzy Stefanowski (SemEval@NAACL-HLT, 2016)

Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data. - Mateusz Lango; Dariusz Brzezinski; Sebastian Firlik; Jerzy Stefanowski (DS, 2017)

Evaluating Difficulty of Multi-class Imbalanced Data. - Mateusz Lango; Krystyna Napierala; Jerzy Stefanowski (ISMIS, 2017)

Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish). - Mateusz Lango; Magda Sevcíková; Zdenek Zabokrtský (LREC, 2018)

ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. - Mateusz Lango; Dariusz Brzezinski; Jerzy Stefanowski (LIDTA@ECML/PKDD, 2018)

Multi-class and feature selection extensions of Roughly Balanced Bagging for imbalanced data. - Mateusz Lango; Jerzy Stefanowski (J. Intell. Inf. Syst., 2018)

Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm. - Malgorzata Janicka; Mateusz Lango; Jerzy Stefanowski (Int. J. Appl. Math. Comput. Sci., 2019)

A Closer Look on Unsupervised Cross-lingual Word Embeddings Mapping. - Kamil Plucinski; Mateusz Lango; Michal Zimniewicz (LREC, 2020)

multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification. - Jacek Grycza; Damian Horna; Hanna Klimczak; Mateusz Lango; Kamil Plucinski; Jerzy Stefanowski (ECML/PKDD (5), 2020)

Time Aspect in Making an Actionable Prediction of a Conversation Breakdown. - Piotr Janiszewski; Mateusz Lango; Jerzy Stefanowski (ECML/PKDD (5), 2021)

Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. - Kamil Plucinski; Mateusz Lango; Jerzy Stefanowski (PKDD/ECML Workshops (1), 2021)

Semi-automatic construction of word-formation networks. - Mateusz Lango; Zdenek Zabokrtský; Magda Sevcíková (Lang. Resour. Evaluation, 2021)

Adversarial oversampling for multi-class imbalanced data classification with convolutional neural networks. - Adam Wojciechowski; Mateusz Lango (LIDTA, 2022)

What makes multi-class imbalanced problems difficult? An experimental study. - Mateusz Lango; Jerzy Stefanowski (Expert Syst. Appl., 2022)

The Problem of Coherence in Natural Language Explanations of Recommendations. - Jakub Raczynski; Mateusz Lango; Jerzy Stefanowski (ECAI, 2023)

Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation. - Mateusz Lango; Ondrej Dusek (EMNLP, 2023)

Generating clickbait spoilers with an ensemble of large language models. - Mateusz Wozny; Mateusz Lango (INLG, 2023)

Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. - Damian Horna; Mateusz Lango; Jerzy Stefanowski (LIDTA, 2023)

Exploiting Phrase Interrelations in Span-level Neural Approaches for Aspect Sentiment Triplet Extraction. - Iwo Naglik; Mateusz Lango (PAKDD (4), 2023)

Alexander Knox at SemEval-2023 Task 5: The comparison of prompting and standard fine-tuning techniques for selecting the type of spoiler needed to neutralize a clickbait. - Mateusz Wozny; Mateusz Lango (SemEval@ACL, 2023)

Three Ways of Using Large Language Models to Evaluate Chat. - Ondrej Plátek; Vojtech Hudecek; Patrícia Schmidtová; Mateusz Lango; Ondrej Dusek (CoRR, 2023)

With a Little Help from the Authors: Reproducing Human Evaluation of an MT Error Detector. - Ondrej Plátek; Mateusz Lango; Ondrej Dusek (CoRR, 2023)

Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish. - Marta Lango; Borys Naglik; Mateusz Lango; Iwo Naglik (LREC/COLING, 2024)

Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs. - Simone Balloccu; Patrícia Schmidtová; Mateusz Lango; Ondrej Dusek (EACL (1), 2024)

ASTE-Transformer: Modelling Dependencies in Aspect-Sentiment Triplet Extraction. - Iwo Naglik; Mateusz Lango (EMNLP (Findings), 2024)

Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline Approach. - Adam Wojciechowski; Mateusz Lango; Ondrej Dusek (EMNLP (Findings), 2024)

Leveraging Large Language Models for Building Interpretable Rule-Based Data-to-Text Systems. - Jedrzej Warczynski; Mateusz Lango; Ondrej Dusek (INLG, 2024)

A multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. - Ignacy Stepka; Mateusz Lango; Jerzy Stefanowski (Int. J. Appl. Math. Comput. Sci., 2024)

A Survey of Text Style Transfer: Applications and Ethical Implications. - Sourabrata Mukherjee; Mateusz Lango; Zdenek Kasner; Ondrej Dusek (CoRR, 2024)

GMMSampling: a new model-based, data difficulty-driven resampling method for multi-class imbalanced data. - Iwo Naglik; Mateusz Lango (Mach. Learn., 2024)

Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change. - Ignacy Stepka; Jerzy Stefanowski; Mateusz Lango (KDD (1), 2025)

Boosting Dual Quality detection with AI-based social media analysis. - Maksim Brzezinski; Maciej Niemir; Krzysztof Muszynski; Mateusz Lango; Dawid Wisniewski (Inf. Process. Manag., 2025)

OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs. - Ivan Kartác; Mateusz Lango; Ondrej Dusek (CoRR, 2025)