Brigita Vileikytė; Mantas Lukoševičius; Lukas Stankevičius
Sentiment Analysis of Lithuanian Online Reviews Using Large Language Models Proceedings Article
In: CEUR workshop proceedings of the 29th international conference on information society and university studies (IVUS 2024) Kaunas, Lithuania, May 17, 2024, pp. 249–258, CEUR-WS 2024.
Links | BibTeX | Tags: Deep learning, Natural language processing, Source code available, Transformers
@inproceedings{Vileikyte2024,
title = {Sentiment Analysis of Lithuanian Online Reviews Using Large Language Models},
author = {Brigita Vileikyt\.{e} and Mantas Luko\v{s}evi\v{c}ius and Lukas Stankevi\v{c}ius},
url = {https://mantas.info/get-publication/?f=Lithuanian_sentiment_analysis_using_LLMs.pdf
https://ceur-ws.org/Vol-3885/paper27.pdf
https://arxiv.org/abs/2407.19914
https://arxiv.org/pdf/2407.19914
https://huggingface.co/brivil1/lithuanian-sentiment-analysis-DistilBERT
https://huggingface.co/brivil1/lithuanian-sentiment-analysis-ByT5
https://www.linkedin.com/posts/lukosevicius_sentiment-analysis-of-lithuanian-online-reviews-activity-7234181985559035906-lUi1},
doi = {10.48550/arXiv.2407.19914},
year = {2024},
date = {2024-07-29},
urldate = {2024-07-29},
booktitle = {CEUR workshop proceedings of the 29th international conference on information society and university studies (IVUS 2024) Kaunas, Lithuania, May 17, 2024},
volume = {3885},
pages = {249--258},
organization = {CEUR-WS},
howpublished = {arXiv},
keywords = {Deep learning, Natural language processing, Source code available, Transformers},
pubstate = {published},
tppubtype = {inproceedings}
}
- https://mantas.info/get-publication/?f=Lithuanian_sentiment_analysis_using_LLMs.[...]
- https://ceur-ws.org/Vol-3885/paper27.pdf
- https://arxiv.org/abs/2407.19914
- https://arxiv.org/pdf/2407.19914
- https://huggingface.co/brivil1/lithuanian-sentiment-analysis-DistilBERT
- https://huggingface.co/brivil1/lithuanian-sentiment-analysis-ByT5
- https://www.linkedin.com/posts/lukosevicius_sentiment-analysis-of-lithuanian-onl[...]
- doi:10.48550/arXiv.2407.19914
Mantas Lukoševičius; Arnas Uselis
Task-Synchronized Recurrent Neural Networks Miscellaneous Forthcoming
arXiv, Forthcoming.
Links | BibTeX | Tags: Deep learning, Reservoir computing, Source code available
@misc{LukoseviciusUselis24,
title = {Task-Synchronized Recurrent Neural Networks},
author = {Mantas Luko\v{s}evi\v{c}ius and Arnas Uselis},
url = {https://mantas.info/get-publication/?f=Task-Syncronized_Recurrent_Neural_Networks.pdf
https://arxiv.org/abs/2204.05192
https://arxiv.org/pdf/2204.05192.pdf
https://github.com/oshapio/task-synchronized-RNNs
https://mantas.info/get-publication/?f=TSRNN_slides.pdf},
doi = {10.48550/arXiv.2204.05192},
year = {2024},
date = {2024-07-02},
urldate = {2024-07-02},
publisher = {arXiv},
howpublished = {arXiv},
keywords = {Deep learning, Reservoir computing, Source code available},
pubstate = {forthcoming},
tppubtype = {misc}
}
Bohdan Petryshyn; Mantas Lukoševičius
Optimizing Large Language Models for OpenAPI Code Completion Miscellaneous Forthcoming
arXiv, Forthcoming.
Links | BibTeX | Tags: Deep learning, Natural language processing, Source code available, Transformers
@misc{PetryshynLukosevicius2024,
title = {Optimizing Large Language Models for OpenAPI Code Completion},
author = {Bohdan Petryshyn and Mantas Luko\v{s}evi\v{c}ius},
url = {https://mantas.info/get-publication/?f=Optimizing_Large_Language_Models_for_OpenAPI_Code_Completion.pdf
https://arxiv.org/abs/2405.15729
https://arxiv.org/pdf/2405.15729
https://paperswithcode.com/paper/optimizing-large-language-models-for-openapi
https://huggingface.co/datasets/BohdanPetryshyn/openapi-completion-refined
https://github.com/BohdanPetryshyn/openapi-completion-benchmark
https://github.com/BohdanPetryshyn/code-llama-fim-fine-tuning
https://www.linkedin.com/posts/lukosevicius_optimizing-large-language-models-for-openapi-activity-7214264622315388928-8QQG},
doi = {10.48550/arXiv.2405.15729},
year = {2024},
date = {2024-06-10},
urldate = {2024-06-10},
howpublished = {arXiv},
keywords = {Deep learning, Natural language processing, Source code available, Transformers},
pubstate = {forthcoming},
tppubtype = {misc}
}
- https://mantas.info/get-publication/?f=Optimizing_Large_Language_Models_for_Open[...]
- https://arxiv.org/abs/2405.15729
- https://arxiv.org/pdf/2405.15729
- https://paperswithcode.com/paper/optimizing-large-language-models-for-openapi
- https://huggingface.co/datasets/BohdanPetryshyn/openapi-completion-refined
- https://github.com/BohdanPetryshyn/openapi-completion-benchmark
- https://github.com/BohdanPetryshyn/code-llama-fim-fine-tuning
- https://www.linkedin.com/posts/lukosevicius_optimizing-large-language-models-for[...]
- doi:10.48550/arXiv.2405.15729
Ana Santos Rodrigues; Rytis Augustauskas; Mantas Lukoševičius; Pablo Laguna; Vaidotas Marozas
Deep-learning-based estimation of the spatial QRS-T angle from reduced-lead ECGs Journal Article
In: Sensors, vol. 22, no. 14, pp. 5414, 2022, ISSN: 1424-8220.
Links | BibTeX | Tags: Biomedicine, Convolutional neural networks, Deep learning, Source code available
@article{ASRodriguesEtAl2022,
title = {Deep-learning-based estimation of the spatial QRS-T angle from reduced-lead ECGs},
author = {Ana Santos Rodrigues and Rytis Augustauskas and Mantas Luko\v{s}evi\v{c}ius and Pablo Laguna and Vaidotas Marozas},
url = {https://mantas.info/get-publication/?f=DL-based_QRS-T_angle_estimation.pdf
https://www.mdpi.com/1734150
https://www.mdpi.com/1424-8220/22/14/5414
https://www.mdpi.com/1424-8220/22/14/5414/pdf?version=1658312326
https://github.com/anarasr/DeepLearningSpatialQRS-Tangle},
doi = {10.3390/s22145414},
issn = {1424-8220},
year = {2022},
date = {2022-07-20},
urldate = {2022-07-20},
journal = {Sensors},
volume = {22},
number = {14},
pages = {5414},
keywords = {Biomedicine, Convolutional neural networks, Deep learning, Source code available},
pubstate = {published},
tppubtype = {article}
}
Lukas Stankevičius; Mantas Lukoševičius
Towards Lithuanian grammatical error correction Proceedings Article
In: Radek Silhavy (Ed.): Artificial Intelligence Trends in Systems, pp. 490–503, Springer, Cham, 2022, ISBN: 978-3-031-09076-9.
Links | BibTeX | Tags: Deep learning, Natural language processing, Source code available, Transformers
@inproceedings{StankeviciusLukosevicius22gec,
title = {Towards Lithuanian grammatical error correction},
author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},
editor = {Radek Silhavy},
url = {https://mantas.info/get-publication/?f=Towards_Lithuanian_Grammatical_Error_Correction.pdf
https://arxiv.org/abs/2203.09963
https://arxiv.org/pdf/2203.09963.pdf
https://doi.org/10.48550/arXiv.2203.09963
https://link.springer.com/chapter/10.1007/978-3-031-09076-9_44
https://github.com/LukasStankevicius/Towards-Lithuanian-Grammatical-Error-Correction
https://huggingface.co/LukasStankevicius/ByT5-Lithuanian-gec-100h
https://paperswithcode.com/paper/towards-lithuanian-grammatical-error},
doi = {10.1007/978-3-031-09076-9_44},
isbn = {978-3-031-09076-9},
year = {2022},
date = {2022-07-08},
urldate = {2022-07-08},
booktitle = {Artificial Intelligence Trends in Systems},
pages = {490--503},
publisher = {Springer},
address = {Cham},
keywords = {Deep learning, Natural language processing, Source code available, Transformers},
pubstate = {published},
tppubtype = {inproceedings}
}
- https://mantas.info/get-publication/?f=Towards_Lithuanian_Grammatical_Error_Corr[...]
- https://arxiv.org/abs/2203.09963
- https://arxiv.org/pdf/2203.09963.pdf
- https://doi.org/10.48550/arXiv.2203.09963
- https://link.springer.com/chapter/10.1007/978-3-031-09076-9_44
- https://github.com/LukasStankevicius/Towards-Lithuanian-Grammatical-Error-Correc[...]
- https://huggingface.co/LukasStankevicius/ByT5-Lithuanian-gec-100h
- https://paperswithcode.com/paper/towards-lithuanian-grammatical-error
- doi:10.1007/978-3-031-09076-9_44
Lukas Stankevičius; Mantas Lukoševičius
Generating abstractive summaries of Lithuanian news articles using a transformer model Proceedings Article
In: International Conference on Information and Software Technologies - ICIST 2021, pp. 341–352, Springer, Cham, 2021, ISBN: 978-3-030-88304-1.
Links | BibTeX | Tags: Deep learning, Natural language processing, Source code available, Transformers
@inproceedings{StankeviciusLukosevicius2021,
title = {Generating abstractive summaries of Lithuanian news articles using a transformer model},
author = {Lukas Stankevi\v{c}ius and Mantas Luko\v{s}evi\v{c}ius},
url = {https://mantas.info/get-publication/?f=Generating_Lithuanian_news_summaries.pdf
https://arxiv.org/abs/2105.03279
https://arxiv.org/pdf/2105.03279.pdf
https://link.springer.com/chapter/10.1007/978-3-030-88304-1_27
https://github.com/LukasStankevicius/Generating-abstractive-summaries-of-Lithuanian-news-articles-using-a-transformer-model
https://huggingface.co/LukasStankevicius/t5-base-lithuanian-news-summaries-175
https://paperswithcode.com/paper/generating-abstractive-summaries-of},
doi = {10.1007/978-3-030-88304-1_27},
isbn = {978-3-030-88304-1},
year = {2021},
date = {2021-10-07},
urldate = {2021-10-07},
booktitle = {International Conference on Information and Software Technologies - ICIST 2021},
pages = {341--352},
publisher = {Springer},
address = {Cham},
keywords = {Deep learning, Natural language processing, Source code available, Transformers},
pubstate = {published},
tppubtype = {inproceedings}
}
- https://mantas.info/get-publication/?f=Generating_Lithuanian_news_summaries.pdf
- https://arxiv.org/abs/2105.03279
- https://arxiv.org/pdf/2105.03279.pdf
- https://link.springer.com/chapter/10.1007/978-3-030-88304-1_27
- https://github.com/LukasStankevicius/Generating-abstractive-summaries-of-Lithuan[...]
- https://huggingface.co/LukasStankevicius/t5-base-lithuanian-news-summaries-175
- https://paperswithcode.com/paper/generating-abstractive-summaries-of
- doi:10.1007/978-3-030-88304-1_27
Mantas Lukoševičius; Arnas Uselis
Efficient implementations of echo state network cross-validation Journal Article
In: Cognitive Computation, vol. 15, iss. 5, pp. 1470-1484, 2021, ISSN: 1866-9964, (Volume date: 2023-09-01).
Links | BibTeX | Tags: Reservoir computing, Source code available
@article{LukoseviciusUselis21,
title = {Efficient implementations of echo state network cross-validation},
author = {Mantas Luko\v{s}evi\v{c}ius and Arnas Uselis},
url = {https://mantas.info/get-publication/?f=Efficient_implement_of_ESN_CV.pdf
https://arxiv.org/abs/2006.11282
https://arxiv.org/pdf/2006.11282.pdf
https://link.springer.com/article/10.1007/s12559-021-09849-2
https://github.com/oshapio/Efficient-Cross-Validation-of-Echo-State-Networks},
doi = {10.1007/s12559-021-09849-2},
issn = {1866-9964},
year = {2021},
date = {2021-03-03},
urldate = {2023-09-01},
journal = {Cognitive Computation},
volume = {15},
issue = {5},
pages = {1470-1484},
note = {Volume date: 2023-09-01},
keywords = {Reservoir computing, Source code available},
pubstate = {published},
tppubtype = {article}
}
- https://mantas.info/get-publication/?f=Efficient_implement_of_ESN_CV.pdf
- https://arxiv.org/abs/2006.11282
- https://arxiv.org/pdf/2006.11282.pdf
- https://link.springer.com/article/10.1007/s12559-021-09849-2
- https://github.com/oshapio/Efficient-Cross-Validation-of-Echo-State-Networks
- doi:10.1007/s12559-021-09849-2
Arnas Uselis; Mantas Lukoševičius; Lukas Stasytis
Localized convolutional neural networks for geospatial wind forecasting Journal Article
In: Energies, vol. 13, no. 13, pp. 3440, 2020.
Links | BibTeX | Tags: Convolutional neural networks, Deep learning, Geospatial, Source code available
@article{UselisLukoseviciusStasytis20,
title = {Localized convolutional neural networks for geospatial wind forecasting },
author = {Arnas Uselis and Mantas Luko\v{s}evi\v{c}ius and Lukas Stasytis},
url = {https://mantas.info/get-publication/?f=Localized_CNNs_for_wind_forecasting.pdf
https://www.mdpi.com/1996-1073/13/13/3440
https://arxiv.org/abs/2005.05930v3
https://arxiv.org/pdf/2005.05930v3.pdf
https://paperswithcode.com/paper/localized-convolutional-neural-networks-for
https://github.com/oshapio/Localized-CNNs-for-Geospatial-Wind-Forecasting
https://mantas.info/get-publication/?f=Localized_CNNs-Gentle_intro_presentation_in_Lithuanian.pdf
https://www.youtube.com/watch?v=cie6lCs1nR4\&Gentle_intro_presentation_in_Lithuanian
},
doi = {10.3390/en13133440},
year = {2020},
date = {2020-07-03},
urldate = {2020-07-03},
issuetitle = {Machine Learning and Deep Learning for Energy Systems},
journal = {Energies},
volume = {13},
number = {13},
pages = {3440},
publisher = {MDPI},
keywords = {Convolutional neural networks, Deep learning, Geospatial, Source code available},
pubstate = {published},
tppubtype = {article}
}
- https://mantas.info/get-publication/?f=Localized_CNNs_for_wind_forecasting.pdf
- https://www.mdpi.com/1996-1073/13/13/3440
- https://arxiv.org/abs/2005.05930v3
- https://arxiv.org/pdf/2005.05930v3.pdf
- https://paperswithcode.com/paper/localized-convolutional-neural-networks-for
- https://github.com/oshapio/Localized-CNNs-for-Geospatial-Wind-Forecasting
- https://mantas.info/get-publication/?f=Localized_CNNs-Gentle_intro_presentation_[...]
- https://www.youtube.com/watch?v=cie6lCs1nR4&Gentle_intro_presentation_in_Lit[...]
- doi:10.3390/en13133440
Mantas Lukoševičius; Vaidotas Marozas
Noninvasive fetal QRS detection using an echo state network and dynamic programming Journal Article
In: Physiological Measurement, vol. 35, no. 8, pp. 1685, 2014.
Links | BibTeX | Tags: Biomedicine, Reservoir computing, Source code available
@article{LukoseviciusMarozas14,
title = {Noninvasive fetal QRS detection using an echo state network and dynamic programming},
author = {Mantas Luko\v{s}evi\v{c}ius and Vaidotas Marozas},
url = {https://mantas.info/get-publication/?f=fetal_QRS_with_ESN_and_DP.pdf
http://iopscience.iop.org/0967-3334/35/8/1685/
https://mantas.info/wp/wp-content/uploads/code/fetal_QRS_with_ESN_and_DP_source_code.zip
https://www.physionet.org/content/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_gmx.com/
https://physionet.org/files/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_gmx.com/},
doi = {10.1088/0967-3334/35/7/1685},
year = {2014},
date = {2014-07-01},
urldate = {2014-07-01},
journal = {Physiological Measurement},
volume = {35},
number = {8},
pages = {1685},
keywords = {Biomedicine, Reservoir computing, Source code available},
pubstate = {published},
tppubtype = {article}
}
- https://mantas.info/get-publication/?f=fetal_QRS_with_ESN_and_DP.pdf
- http://iopscience.iop.org/0967-3334/35/8/1685/
- https://mantas.info/wp/wp-content/uploads/code/fetal_QRS_with_ESN_and_DP_source_[...]
- https://www.physionet.org/content/challenge-2013/1.0.0/sources/mantas.lukosevici[...]
- https://physionet.org/files/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_[...]
- doi:10.1088/0967-3334/35/7/1685
Mantas Lukoševičius; Vaidotas Marozas
Noninvasive Fetal QRS Detection using Echo State Network Proceedings Article
In: Proceedings of Computing in Cardiology 2013, pp. 205-208, 2013.
Links | BibTeX | Tags: Biomedicine, Reservoir computing, Source code available
@inproceedings{LukoseviciusMarozas13,
title = {Noninvasive Fetal QRS Detection using Echo State Network},
author = {Mantas Luko\v{s}evi\v{c}ius and Vaidotas Marozas},
url = {https://mantas.info/get-publication/?f=fetal_QRS_with_ESN.pdf
http://cinc.org/archives/2013/pdf/0205.pdf
https://www.physionet.org/content/challenge-2013/1.0.0/papers/0205.pdf
https://ieeexplore.ieee.org/abstract/document/6712447
https://mantas.info/wp/wp-content/uploads/code/fetal_QRS_with_ESN_and_DP_source_code.zip
https://www.physionet.org/content/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_gmx.com/
https://physionet.org/files/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_gmx.com/},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
booktitle = {Proceedings of Computing in Cardiology 2013},
volume = {40},
pages = {205-208},
keywords = {Biomedicine, Reservoir computing, Source code available},
pubstate = {published},
tppubtype = {inproceedings}
}
- https://mantas.info/get-publication/?f=fetal_QRS_with_ESN.pdf
- http://cinc.org/archives/2013/pdf/0205.pdf
- https://www.physionet.org/content/challenge-2013/1.0.0/papers/0205.pdf
- https://ieeexplore.ieee.org/abstract/document/6712447
- https://mantas.info/wp/wp-content/uploads/code/fetal_QRS_with_ESN_and_DP_source_[...]
- https://www.physionet.org/content/challenge-2013/1.0.0/sources/mantas.lukosevici[...]
- https://physionet.org/files/challenge-2013/1.0.0/sources/mantas.lukosevicius_at_[...]
Mantas Lukoševičius
A practical guide to applying echo state networks Book Section
In: Grégoire Montavon; Geneviève B. Orr; Klaus-Robert Müller (Ed.): Neural Networks: Tricks of the Trade, 2nd Edition, vol. 7700, pp. 659-686, Springer, 2012, ISBN: 978-3-642-35288-1, (simple source code samples available).
Links | BibTeX | Tags: Reservoir computing, Source code available
@incollection{Lukosevicius12a,
title = {A practical guide to applying echo state networks},
author = {Mantas Luko\v{s}evi\v{c}ius},
editor = {Gr\'{e}goire Montavon and Genevi\`{e}ve B. Orr and Klaus-Robert M\"{u}ller},
url = {https://mantas.info/get-publication/?f=Practical_ESN.pdf
http://link.springer.com/chapter/10.1007%2F978-3-642-35289-8_36
https://www.ai.rug.nl/minds/uploads/PracticalESN.pdf
/code/simple_esn/},
doi = {10.1007/978-3-642-35289-8_36},
isbn = {978-3-642-35288-1},
year = {2012},
date = {2012-01-01},
booktitle = {Neural Networks: Tricks of the Trade, 2nd Edition},
volume = {7700},
pages = {659-686},
publisher = {Springer},
series = {LNCS},
note = {simple source code samples available},
keywords = {Reservoir computing, Source code available},
pubstate = {published},
tppubtype = {incollection}
}
Herbert Jaeger; Mantas Lukoševičius; Dan Popovici; Udo Siewert
Optimization and applications of echo state networks with leaky-integrator neurons Journal Article
In: Neural Networks, vol. 20, no. 3, pp. 335-352, 2007.
Links | BibTeX | Tags: Reservoir computing, Source code available
@article{JaegerEtAl07si,
title = {Optimization and applications of echo state networks with leaky-integrator neurons},
author = {Herbert Jaeger and Mantas Luko\v{s}evi\v{c}ius and Dan Popovici and Udo Siewert},
url = {https://mantas.info/get-publication/?f=leakyESN.pdf
http://www.sciencedirect.com/science/article/pii/S089360800700041X
https://www.ai.rug.nl/minds/uploads/leakyESN.pdf
https://www.ai.rug.nl/minds/uploads/JapVowels_forWeb.zip
https://www.ai.rug.nl/minds/uploads/parameterOptimization_forWeb.zip},
doi = {10.1016/j.neunet.2007.04.016},
year = {2007},
date = {2007-01-01},
urldate = {2007-01-01},
journal = {Neural Networks},
volume = {20},
number = {3},
pages = {335-352},
keywords = {Reservoir computing, Source code available},
pubstate = {published},
tppubtype = {article}
}
- https://mantas.info/get-publication/?f=leakyESN.pdf
- http://www.sciencedirect.com/science/article/pii/S089360800700041X
- https://www.ai.rug.nl/minds/uploads/leakyESN.pdf
- https://www.ai.rug.nl/minds/uploads/JapVowels_forWeb.zip
- https://www.ai.rug.nl/minds/uploads/parameterOptimization_forWeb.zip
- doi:10.1016/j.neunet.2007.04.016
Local versions of paywalled articles are preprints.
My publications in Google Scholar.