For more details, see my Google Scholar profile.
- Lango M., Naglik B., Lango M., Naglik I., Polish-ASTE: New Aspect-Sentiment Triplet Extraction Datasets for Polish, LREC-COLING, 2024 dataset
- Balloccu S., Schmidtová P., Lango M., Dušek O., Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-source LLMs, 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Malta, 2024 website Best Non-publicized Paper award
- Stępka I., Lango M., Stefanowski J., Multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers, International Journal of Applied Mathematics and Computer Science, 2024 appendix
- Lango M., Dušek O., Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation, Empirical Methods in Natural Language Processing (EMNLP), Singapore, 2023 code
- Naglik I., Lango M., GMMSampling: a new model-based, data difficulty-driven resampling method for multi-class imbalanced data, Machine Learning Journal, Springer, 2023 appendix code
- Plátek O., Lango M., Dušek O., With a Little Help from the Authors: Reproducing Human Evaluation of an MT Error Detector, The 3rd Workshop on Human Evaluation of NLP Systems (HumEval’23) co-located with RANLP, Varna, Bulgaria, 2023 code
- Raczyński J., Lango M., Stefanowski J., The Problem of Coherence in Natural Language Explanations of Recommendations, European Conference on Artificial Intelligence (ECAI), Kraków, Poland, 2023 code appendix
- Woźny M., Lango M., Generating clickbait spoilers with an ensemble of large language models, 16th International Natural Language Generation Conference (INLG'23), Prague, Czech Republic, 2023 appendix
- Plátek O., Hudeček V., Schmidtová P., Lango M., Dušek O., Three Ways of Using Large Language Models to Evaluate Chat, DSTC11: The Eleventh Dialog System Technology Challenge co-located with SIGDIAL-INLG, Prague, Czech Republic, 2023
- Horna D., Lango M., Stefanowski J., Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance, JMLR Proceedings of the 5th International Workshop on Learning with Imbalanced Domains co-located with ECML/PKDD, Torino, Italy, 2023
- Woźny M., Lango M., The comparison of prompting and standard fine-tuning techniques for selecting the type of spoiler needed to neutralize a clickbait, The 17th International Workshop on Semantic Evaluation (SemEval '23) co-located with ACL-2023, Toronto, Canada, 2023
- Stępka I., Lango M., Stefanowski J., On usefulness of dominance relation for selecting counterfactuals from the ensemble of explainers, Polish Conference on Artificial Intelligence (PP-RAI '23), Łódź, Poland, 2023
- Naglik I., Lango M., Exploiting Phrase Interrelations in Span-level Neural Approaches for Aspect Sentiment Triplet Extraction , Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023), Osaka, Japan, 2023 appendix code
- Marynowicz J., Lango M., Horna D., Kikut K., Konefał M., Chmura P., Andrzejewski M., Within-Subject Principal Component Analysis of External Training Load and Intensity Measures in Youth Soccer Training, Journal of Strength and Conditioning Research, 2023
- Wojciechowski A., Lango M., Adversarial oversampling for multi-class imbalanced data classification with convolutional neural networks, JMLR Proceedings of the 4th International Workshop on Learning with Imbalanced Domains co-located with ECML/PKDD, Grenoble, France, 2022 appendix
- Andrzejewski M., Iżemski A., Linkowski P., Pluciński K., Szpotański E., Lango M., Jędrzejewski K., Can reinforcement learning agents be e-teachers? Application of machine learning in education, Polish Conference on Artificial Intelligence (PP-RAI '22), Gdynia, Poland, 2022
- Lango M., Stefanowski J., What makes multi-class imbalanced problems difficult? An experimental study., Expert Systems With Applications, 2022
- Pluciński K., Lango M., Stefanowski J., Prototypical Convolutional Neural Network for a phrase-based explanation of sentiment classification, ECML PKDD International Workshop and Tutorial on eXplainable Knowledge Discovery in Data Mining (XKDD), 2021
- Janiszewski P., Lango M., Stefanowski J., Time aspect in making an actionable prediction of a conversation breakdown, European Conference on Machine Learning (ECML-PKDD), 2021
- Marynowicz J., Lango M., Horna D., Kikut K., Andrzejewski M., Predicting ratings of perceived exertion in youth soccer using decision tree models, Biology of Sport, 2021
- Marynowicz J., Kikut K., Lango M., Horna D., Andrzejewski M., Relationship between the Session-RPE and external measures of training load in youth soccer training, Journal of Strength and Conditioning Research, 2020
- Grycza J., Horna D., Klimczak H., Lango M., Pluciński K, Stefanowski J., multi-imbalance: open source Python toolbox for multi-class imbalanced classification, European Conference on Machine Learning (ECML-PKDD), Ghent, Belgium, 2020 webpage
- Marynowicz J., Kikut K., Lango M., Horna D., Andrzejewski M., Relationship between the Session-RPE and external measures of training load in youth soccer training, European College of Sport Science (ECSS) congress, Sevilla, Spain, 2020
- Pluciński K., Lango M., Zimniewicz M., A Closer Look on Unsupervised Cross-lingual Word Embeddings Mapping, Proceedings of the 12th International Conference on Language Resources and Evaluation, Marseille, France, 2020
- Lango M., Žabokrtský Z., Ševčíková M. Semi-Automatic Construction of Word-Formation Networks,
Language Resources and Evaluation, 2020 data resource DeriSearch online
- Lango M., Stefanowski J., SOUP-Bagging: a new approach for multi-class imbalanced data classification, PP-RAI '19: Polskie Porozumienie na Rzecz Sztucznej Inteligencji, 2019
- Janicka M., Lango M., Stefanowski J., Using information on class interrelations to improve classification of multi-class imbalanced data: a new re-sampling algorithm, International Journal of Applied Mathematics and Computer Science, 2019 appendix
- Lango M., Tackling the Problem of Class Imbalance in Multi-class Sentiment Classification: An Experimental Study, Foundations of Computing and Decision Sciences, 2019 appendix
- Lango M., Brzeziński D., Stefanowski J., ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information, JMLR Proceedings of the 2nd International Workshop on Learning with Imbalanced Domains co-located with ECML/PKDD, Dublin, Ireland, 2018 appendix slides
- Lango M., Ševčíková M., Žabokrtský Z., Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish), Proceedings of the 11th International Conference on Language Resources and Evaluation, Miyazaki, Japan, 2018 data resource DeriSearch online
- Lango M., Brzeziński D., Firlik S., Stefanowski J., Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data, Proceedings of the 20th International Conference on Discovery Science, Kyoto, Japan, 2017 appendix code
- Lango M., Napierala K., Stefanowski J., Evaluating difficulty of multi-class imbalanced data, Foundations of Intelligent Systems, Lecture Notes in Artificial Intelligence, Springer, 2017 appendix
- Lango M., Stefanowski J., Multi-class and Feature Selection Extensions of Roughly Balanced Bagging for Imbalanced Data, Journal of Intelligent Information Systems, 2017
- Lango M., Brzeziński D., Stefanowski J., PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis, Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval 2016), San Diego, US , 2016
- Błaszczyński J., Lango M., Diversity Analysis on Imbalanced Data Using Neighbourhood and Roughly Balanced Bagging Ensembles, Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, Springer , 2016
- Lango M., Stefanowski J., The Usefulness of Roughly Balanced Bagging for Complex and High-dimensional Imbalanced Data, In New Frontiers in Mining Complex Patterns, Lecture Notes in Computer Science, Springer , 2016
- Lango M., Stefanowski J., Applicability of Roughly Balanced Bagging for Complex Imbalanced Data, Proceedings of the 4th Workshop on New Frontiers in Mining Complex Patterns join together with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015
Dissertations
- Lango M., Analysis of data difficulty factors for multi-class imbalanced problems and their application in classification methods, Poznan Univeristy of Technology, 2022 (PhD Thesis)
- Lango M., Analysis and Extensions of Roughly Balanced Bagging Ensemble for Imbalanced Data, Poznan Univeristy of Technology, 2015 (MSc Thesis)
- Charoński T., Grabowska M., Lango M., Lewiński J., Scholar+: Extending Google Scholar with Web of Science filter, Poznan Univeristy of Technology, 2014 (BSc Thesis)
Other publications
- Wiliński M., Lango M., Naglik I.: Towards Explainable and Scalable Aspect-based Sentiment Analysis: A Linear-Time Transition-Based Framework, MLinPL Conference, 2023
- Wojciechowski A., Lango M.: Adversarial OverSampling for imbalanced image data classification, MLinPL Virtual Meeting, 2020 (poster, 2nd place in Best Poster Competition)
- Pluciński K., Lango M.: Unsupervised Machine Translation, MLinPL Conference, 2019 (poster, Best Poster Audience Award)
- Literature-based discovery at scale! (article, p. 58-60)
- The secret of Big Data programmers (blog post)
- Introducing LBDream and Literature-based discovery (blog post)