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Mateusz Lango
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2020 – today
- 2024
- [j6]Ignacy Stepka
, Mateusz Lango, Jerzy Stefanowski
:
A multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. Int. J. Appl. Math. Comput. Sci. 34(1) (2024) - [j5]Iwo Naglik, Mateusz Lango
:
GMMSampling: a new model-based, data difficulty-driven resampling method for multi-class imbalanced data. Mach. Learn. 113(8): 5183-5202 (2024) - [c23]Marta Lango, Borys Naglik, Mateusz Lango, Iwo Naglik:
Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish. LREC/COLING 2024: 12821-12828 - [c22]Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, Ondrej Dusek:
Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs. EACL (1) 2024: 67-93 - [c21]Iwo Naglik, Mateusz Lango:
ASTE-Transformer: Modelling Dependencies in Aspect-Sentiment Triplet Extraction. EMNLP (Findings) 2024: 2324-2339 - [c20]Adam Wojciechowski, Mateusz Lango, Ondrej Dusek:
Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline Approach. EMNLP (Findings) 2024: 2340-2351 - [c19]Jedrzej Warczynski, Mateusz Lango, Ondrej Dusek:
Leveraging Large Language Models for Building Interpretable Rule-Based Data-to-Text Systems. INLG 2024: 622-630 - [i12]Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, Ondrej Dusek:
Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs. CoRR abs/2402.03927 (2024) - [i11]Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski:
Multi-criteria approach for selecting an explanation from the set of counterfactuals produced by an ensemble of explainers. CoRR abs/2403.13940 (2024) - [i10]Mateusz Wozny, Mateusz Lango:
Generating clickbait spoilers with an ensemble of large language models. CoRR abs/2405.16284 (2024) - [i9]Sourabrata Mukherjee, Mateusz Lango, Zdenek Kasner, Ondrej Dusek:
A Survey of Text Style Transfer: Applications and Ethical Implications. CoRR abs/2407.16737 (2024) - [i8]Adam Wojciechowski, Mateusz Lango, Ondrej Dusek:
Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline Approach. CoRR abs/2407.20899 (2024) - [i7]Ignacy Stepka, Mateusz Lango, Jerzy Stefanowski:
Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change. CoRR abs/2408.04842 (2024) - [i6]Iwo Naglik, Mateusz Lango:
ASTE Transformer Modelling Dependencies in Aspect-Sentiment Triplet Extraction. CoRR abs/2409.15202 (2024) - 2023
- [c18]Jakub Raczynski, Mateusz Lango
, Jerzy Stefanowski
:
The Problem of Coherence in Natural Language Explanations of Recommendations. ECAI 2023: 1922-1929 - [c17]Mateusz Lango
, Ondrej Dusek:
Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation. EMNLP 2023: 2853-2862 - [c16]Mateusz Wozny, Mateusz Lango
:
Generating clickbait spoilers with an ensemble of large language models. INLG 2023: 431-436 - [c15]Damian Horna, Mateusz Lango, Jerzy Stefanowski:
Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. LIDTA 2023: 1-15 - [c14]Iwo Naglik
, Mateusz Lango
:
Exploiting Phrase Interrelations in Span-level Neural Approaches for Aspect Sentiment Triplet Extraction. PAKDD (4) 2023: 222-233 - [c13]Mateusz Wozny, Mateusz Lango
:
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. SemEval@ACL 2023: 1470-1475 - [i5]Ondrej Plátek, Vojtech Hudecek, Patrícia Schmidtová, Mateusz Lango, Ondrej Dusek:
Three Ways of Using Large Language Models to Evaluate Chat. CoRR abs/2308.06502 (2023) - [i4]Ondrej Plátek, Mateusz Lango, Ondrej Dusek:
With a Little Help from the Authors: Reproducing Human Evaluation of an MT Error Detector. CoRR abs/2308.06527 (2023) - [i3]Mateusz Lango, Ondrej Dusek:
Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation. CoRR abs/2310.16964 (2023) - [i2]Damian Horna, Mateusz Lango, Jerzy Stefanowski
:
Deep Similarity Learning Loss Functions in Data Transformation for Class Imbalance. CoRR abs/2312.10556 (2023) - [i1]Jakub Raczynski, Mateusz Lango, Jerzy Stefanowski:
The Problem of Coherence in Natural Language Explanations of Recommendations. CoRR abs/2312.11356 (2023) - 2022
- [j4]Mateusz Lango
, Jerzy Stefanowski
:
What makes multi-class imbalanced problems difficult? An experimental study. Expert Syst. Appl. 199: 116962 (2022) - [c12]Adam Wojciechowski, Mateusz Lango
:
Adversarial oversampling for multi-class imbalanced data classification with convolutional neural networks. LIDTA 2022: 98-111 - 2021
- [j3]Mateusz Lango
, Zdenek Zabokrtský
, Magda Sevcíková:
Semi-automatic construction of word-formation networks. Lang. Resour. Evaluation 55(1): 3-32 (2021) - [c11]Piotr Janiszewski, Mateusz Lango
, Jerzy Stefanowski
:
Time Aspect in Making an Actionable Prediction of a Conversation Breakdown. ECML/PKDD (5) 2021: 351-364 - [c10]Kamil Plucinski, Mateusz Lango
, Jerzy Stefanowski
:
Prototypical Convolutional Neural Network for a Phrase-Based Explanation of Sentiment Classification. PKDD/ECML Workshops (1) 2021: 457-472 - 2020
- [c9]Kamil Plucinski, Mateusz Lango, Michal Zimniewicz:
A Closer Look on Unsupervised Cross-lingual Word Embeddings Mapping. LREC 2020: 5555-5562 - [c8]Jacek Grycza, Damian Horna, Hanna Klimczak, Mateusz Lango
, Kamil Plucinski, Jerzy Stefanowski
:
multi-imbalance: Open Source Python Toolbox for Multi-class Imbalanced Classification. ECML/PKDD (5) 2020: 546-549
2010 – 2019
- 2019
- [j2]Malgorzata Janicka, Mateusz Lango
, Jerzy Stefanowski:
Using Information on Class Interrelations to Improve Classification of Multiclass Imbalanced Data: A New Resampling Algorithm. Int. J. Appl. Math. Comput. Sci. 29(4): 769-781 (2019) - 2018
- [j1]Mateusz Lango
, Jerzy Stefanowski
:
Multi-class and feature selection extensions of Roughly Balanced Bagging for imbalanced data. J. Intell. Inf. Syst. 50(1): 97-127 (2018) - [c7]Mateusz Lango, Magda Sevcíková, Zdenek Zabokrtský:
Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish). LREC 2018 - [c6]Mateusz Lango, Dariusz Brzezinski, Jerzy Stefanowski:
ImWeights: Classifying Imbalanced Data Using Local and Neighborhood Information. LIDTA@ECML/PKDD 2018: 95-109 - 2017
- [c5]Mateusz Lango
, Dariusz Brzezinski
, Sebastian Firlik, Jerzy Stefanowski
:
Discovering Minority Sub-clusters and Local Difficulty Factors from Imbalanced Data. DS 2017: 324-339 - [c4]Mateusz Lango
, Krystyna Napierala, Jerzy Stefanowski
:
Evaluating Difficulty of Multi-class Imbalanced Data. ISMIS 2017: 312-322 - 2016
- [c3]Jerzy Blaszczynski
, Mateusz Lango
:
Diversity Analysis on Imbalanced Data Using Neighbourhood and Roughly Balanced Bagging Ensembles. ICAISC (1) 2016: 552-562 - [c2]Mateusz Lango
, Dariusz Brzezinski
, Jerzy Stefanowski
:
PUT at SemEval-2016 Task 4: The ABC of Twitter Sentiment Analysis. SemEval@NAACL-HLT 2016: 126-132 - 2015
- [c1]Mateusz Lango
, Jerzy Stefanowski
:
The Usefulness of Roughly Balanced Bagging for Complex and High-Dimensional Imbalanced Data. NFMCP 2015: 93-107
Coauthor Index
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