Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
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 and potential bias; scores should be interpreted as estimates.
The Complexity Landscape of Claim-Augmented Argumentation Frameworks
Authors: Wolfgang Dvořák, Alexander Greßler, Anna Rapberger, Stefan Woltran6296-6303
AAAI 2021 | Venue PDF | LLM Run Details | Input Tokens: 18,566 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 4,635 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | To this end, we provide a comprehensive complexity analysis of the four main reasoning problems with respect to claim-level variants of preferred, naive, stable, semi-stable and stage semantics and complete the complexity results of inherited semantics by providing corresponding results for semi-stable and stage semantics. Our main contributions are as follows: We settle the computational complexity of all the claim-level semantics... |
| Researcher Affiliation | Academia | Wolfgang Dvoˇr ak, Alexander Greßler, Anna Rapberger, Stefan Woltran TU Wien, Institute of Logic and Computation, Austria EMAIL |
| Pseudocode | No | The paper does not contain any pseudocode or algorithm blocks. It focuses on theoretical proofs and complexity analysis. |
| Open Source Code | No | The paper does not provide any links to open-source code or state that code for their methodology is available. |
| Open Datasets | No | This paper is theoretical and does not involve empirical evaluation with datasets. |
| Dataset Splits | No | This paper is theoretical and does not involve empirical evaluation with datasets or data splitting. |
| Hardware Specification | No | This is a theoretical paper focusing on complexity analysis and does not describe any experiments that would require hardware specifications. |
| Software Dependencies | No | This paper is theoretical and does not describe any software implementations or their dependencies. |
| Experiment Setup | No | This paper is theoretical and does not describe any experimental setup, hyperparameters, or training configurations. |