@inproceedings{binder-etal-2024-dfki,
title = "{DFKI}-{MLST} at {D}ial{AM}-2024 Shared Task: System Description",
author = "Binder, Arne and
Anikina, Tatiana and
Hennig, Leonhard and
Ostermann, Simon",
editor = "Ajjour, Yamen and
Bar-Haim, Roy and
El Baff, Roxanne and
Liu, Zhexiong and
Skitalinskaya, Gabriella",
booktitle = "Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.argmining-1.9",
pages = "93--102",
abstract = "This paper presents the dfki-mlst submission for the DialAM shared task (Ruiz-Dolz et al., 2024) on identification of argumentative and illocutionary relations in dialogue. Our model achieves best results in the global setting: 48.25 F1 at the focused level when looking only at the related arguments/locutions and 67.05 F1 at the general level when evaluating the complete argument maps. We describe our implementation of the data pre-processing, relation encoding and classification, evaluating 11 different base models and performing experiments with, e.g., node text combination and data augmentation. Our source code is publicly available.",
}
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<abstract>This paper presents the dfki-mlst submission for the DialAM shared task (Ruiz-Dolz et al., 2024) on identification of argumentative and illocutionary relations in dialogue. Our model achieves best results in the global setting: 48.25 F1 at the focused level when looking only at the related arguments/locutions and 67.05 F1 at the general level when evaluating the complete argument maps. We describe our implementation of the data pre-processing, relation encoding and classification, evaluating 11 different base models and performing experiments with, e.g., node text combination and data augmentation. Our source code is publicly available.</abstract>
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%0 Conference Proceedings
%T DFKI-MLST at DialAM-2024 Shared Task: System Description
%A Binder, Arne
%A Anikina, Tatiana
%A Hennig, Leonhard
%A Ostermann, Simon
%Y Ajjour, Yamen
%Y Bar-Haim, Roy
%Y El Baff, Roxanne
%Y Liu, Zhexiong
%Y Skitalinskaya, Gabriella
%S Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F binder-etal-2024-dfki
%X This paper presents the dfki-mlst submission for the DialAM shared task (Ruiz-Dolz et al., 2024) on identification of argumentative and illocutionary relations in dialogue. Our model achieves best results in the global setting: 48.25 F1 at the focused level when looking only at the related arguments/locutions and 67.05 F1 at the general level when evaluating the complete argument maps. We describe our implementation of the data pre-processing, relation encoding and classification, evaluating 11 different base models and performing experiments with, e.g., node text combination and data augmentation. Our source code is publicly available.
%U https://aclanthology.org/2024.argmining-1.9
%P 93-102
Markdown (Informal)
[DFKI-MLST at DialAM-2024 Shared Task: System Description](https://aclanthology.org/2024.argmining-1.9) (Binder et al., ArgMining 2024)
ACL
- Arne Binder, Tatiana Anikina, Leonhard Hennig, and Simon Ostermann. 2024. DFKI-MLST at DialAM-2024 Shared Task: System Description. In Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024), pages 93–102, Bangkok, Thailand. Association for Computational Linguistics.