Ing.

Martin Fajčík

FIT, DCGM

+420 54114 1421
ifajcik@fit.vut.cz

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Ing. Martin Fajčík

Publications

  • 2023

    FAJČÍK, M.; MOTLÍČEK, P.; SMRŽ, P. Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Prediction. In Findings of the Association for Computational Linguistics: ACL 2023. ACL. Toronto: Association for Computational Linguistics, 2023. p. 10184-10205. ISBN: 978-1-959429-62-3.
    Detail | WWW

  • 2022

    BURDISSO, S.; FAJČÍK, M.; SMRŽ, P.; MOTLÍČEK, P. IDIAPers @ Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach. In Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022). Abu Dhabi: Association for Computational Linguistics, 2022. p. 61-69. ISBN: 978-1-959429-05-0.
    Detail | WWW

    FAJČÍK, M.; SMRŽ, P.; MOTLÍČEK, P.; BURDISSO, S. IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model. In Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022). Abu Dhabi: Association for Computational Linguistics, 2022. p. 70-78. ISBN: 978-1-959429-05-0.
    Detail | WWW

  • 2021

    FAJČÍK, M.; DOČEKAL, M.; ONDŘEJ, K.; SMRŽ, P. R2-D2: A Modular Baseline for Open-Domain Question Answering. In Findings of the Association for Computational Linguistics: EMNLP 2021. Findings of the Association for Computational Linguistics. Punta Cana: Association for Computational Linguistics, 2021. p. 854-870. ISBN: 978-1-955917-10-0.
    Detail | WWW

    FAJČÍK, M.; JON, J.; SMRŽ, P. Rethinking the Objectives of Extractive Question Answering. In Proceedings of the 3rd Workshop on Machine Reading for Question Answering. Proceedings of the 3rd Workshop on Machine Reading for Question Answering. Punta Cana: Association for Computational Linguistics, 2021. p. 14-27. ISBN: 978-1-954085-95-4.
    Detail | WWW

    MIN, S.; FAJČÍK, M.; DOČEKAL, M.; ONDŘEJ, K.; SMRŽ, P. NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. Proceedings of the NeurIPS 2020 Competition and Demonstration Track. Proceedings of Machine Learning Research. online: Proceedings of Machine Learning Research, 2021. p. 86-111. ISSN: 2640-3498.
    Detail | WWW

  • 2020

    DOČEKAL, M.; FAJČÍK, M.; JON, J.; SMRŽ, P. JokeMeter at SemEval-2020 Task 7: Convolutional Humor. In Proceedings of the Fourteenth Workshop on Semantic Evaluation. 2020. Barcelona (online): Association for Computational Linguistics, 2020. p. 843-851. ISBN: 978-1-952148-31-6.
    Detail | WWW

    JON, J.; FAJČÍK, M.; DOČEKAL, M.; SMRŽ, P. BUT-FIT at SemEval-2020 Task 4: Multilingual commonsense. In Proceedings of the Fourteenth Workshop on Semantic Evaluation. Barcelona: Association for Computational Linguistics, 2020. p. 374-390. ISBN: 978-1-952148-31-6.
    Detail | WWW

    FAJČÍK, M.; DOČEKAL, M.; JON, J.; SMRŽ, P. BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models. In Proceedings of the Fourteenth Workshop on Semantic Evaluation. Barcelona (online): Association for Computational Linguistics, 2020. p. 437-444. ISBN: 978-1-952148-31-6.
    Detail | WWW

  • 2019

    FAJČÍK, M.; BURGET, L.; SMRŽ, P. BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers. In Proceedings of the 13th International Workshop on Semantic Evaluation. Minneapolis, Minnesota: Association for Computational Linguistics, 2019. p. 1097-1104. ISBN: 978-1-950737-06-2.
    Detail | WWW

  • 2017

    FAJČÍK, M.; SMRŽ, P.; ZACHARIÁŠOVÁ, M. Automation of Processor Verification Using Recurrent Neural Networks. In 18th International Workshop on Microprocessor and SOC Test, Security and Verification (MTV). Austin, Texas: Institute of Electrical and Electronics Engineers, 2017. p. 15-20. ISBN: 978-1-5386-3351-9.
    Detail | WWW

*) Publications are generated once a 24 hours.