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.
Safe Inductions: An Algebraic Study
Authors: Bart Bogaerts, Joost Vennekens, Marc Denecker
IJCAI 2017 | Venue PDF | LLM Run Details | Input Tokens: 17,123 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 2,656 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 | In this paper, we formally deο¬ne the safety criterion algebraically. We study properties of so-called safe inductions and apply our theory to logic programming and autoepistemic logic. |
| Researcher Affiliation | Academia | Bart Bogaerts and Joost Vennekens and Marc Denecker KU Leuven, Department of Computer Science Celestijnenlaan 200A, Leuven, Belgium |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not use datasets for training or experimentation, therefore no access information for such datasets is provided. |
| Dataset Splits | No | The paper is theoretical and does not describe empirical experiments involving dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe empirical experiments, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and focuses on abstract algebraic theory, not on specific software implementations or their versions. |
| Experiment Setup | No | The paper is theoretical and does not describe empirical experiments, thus no experimental setup details like hyperparameters or training configurations are provided. |