no code implementations • ArgMining (ACL) 2022 • Philipp Heinisch, Moritz Plenz, Juri Opitz, Anette Frank, Philipp Cimiano
Using only training data retrieved from related datasets by automatically labeling them for validity and novelty, combined with synthetic data, outperforms the baseline by 11. 5 points in F_1-score.
1 code implementation • ArgMining (ACL) 2022 • Philipp Heinisch, Anette Frank, Juri Opitz, Moritz Plenz, Philipp Cimiano
This paper provides an overview of the Argument Validity and Novelty Prediction Shared Task that was organized as part of the 9th Workshop on Argument Mining (ArgMining 2022).
Ranked #1 on ValNov on ValNov Subtask A
1 code implementation • 13 Jan 2024 • Moritz Plenz, Anette Frank
In our work we introduce a novel LM type, the Graph Language Model (GLM), that integrates the strengths of both approaches and mitigates their weaknesses.
1 code implementation • 15 May 2023 • Moritz Plenz, Juri Opitz, Philipp Heinisch, Philipp Cimiano, Anette Frank
Arguments often do not make explicit how a conclusion follows from its premises.