Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
Investigating the Relationship between Argumentation Semantics via Signatures
Authors: Paul E. Dunne, Christof Spanring, Thomas Linsbichler, Stefan Woltran
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We investigate in total nine argumentation semantics and give a nearly complete landscape of exact characterizations. As we shall argue, such results not only give an account on the independency between semantics, but might also prove useful in argumentation systems by providing guidelines for how to prune the search space. |
| Researcher Affiliation | Academia | Paul E. Dunne and Christof Spanring Department of Computer Science University of Liverpool, UK EMAIL Thomas Linsbichler and Stefan Woltran Institute of Information Systems TU Wien, Vienna, Austria EMAIL |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and focuses on characterizing relationships between argumentation semantics rather than training models on empirical datasets. Therefore, there is no information about dataset availability or access for training purposes. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset validation splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for its work. |
| Software Dependencies | No | The paper is theoretical and does not provide specific ancillary software details with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with specific hyperparameters or system-level training settings. |