DFKI-MLST at DialAM-2024 Shared Task: System Description
Arne Binder, Tatiana Anikina, Leonhard Hennig, Simon Ostermann
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.- Anthology ID:
- 2024.argmining-1.9
- Volume:
- Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Yamen Ajjour, Roy Bar-Haim, Roxanne El Baff, Zhexiong Liu, Gabriella Skitalinskaya
- Venue:
- ArgMining
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 93–102
- Language:
- URL:
- https://aclanthology.org/2024.argmining-1.9
- DOI:
- Cite (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.
- Cite (Informal):
- DFKI-MLST at DialAM-2024 Shared Task: System Description (Binder et al., ArgMining 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.argmining-1.9.pdf