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.
Multiple Constraint Acquisition
Authors: Robin Arcangioli, Christian Bessiere, Nadjib Lazaar
IJCAI 2016 | Venue PDF | LLM Run Details | Input Tokens: 15,760 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,200 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We made experiments to evaluate the performance of MULTIACQ and its find All Scopes function compared to QUACQ. We also evaluate the version using cut-offs, that we call MACQ-CO (i.e., MULTIAcq with Cuts-Offs). |
| Researcher Affiliation | Academia | Robin Arcangioli, Christian Bessiere, Nadjib Lazaar CNRS, University of Montpellier, France |
| Pseudocode | Yes | Algorithme 1 : MULTIACQ |
| Open Source Code | No | The paper does not provide explicit access to its source code (e.g., a repository link or a statement about code release in supplementary materials). |
| Open Datasets | Yes | CSPLib : a benchmark library for constraints. http://www.csplib.org/, 1999. |
| Dataset Splits | No | The paper describes an active learning process where the system interactively queries the user for examples. It does not define traditional train/validation/test splits for datasets, as examples are generated and classified on the fly during the acquisition process. |
| Hardware Specification | Yes | Our tests were conducted on an 1,6 GHz Intel Core i5 with 4.0GB of RAM (1600 MHz DDR3). |
| Software Dependencies | No | The paper mentions the names of systems like QUACQ, MULTIACQ, and MACQ-CO, and concepts like constraint programming and SAT, but it does not specify any particular software dependencies with version numbers (e.g., specific libraries, compilers, or operating systems). |
| Experiment Setup | Yes | The cutoff on the time between two queries has been set to 5 seconds. This is an acceptable waiting time for a human user. We combine the cutoff technique with a second heuristic based on reordering the variables. |