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 and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Soft and Cost MDD Propagators
Authors: Guillaume Perez, Jean-Charles RΒgin
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In the experimental section, we give some results for the complex text generation problem that motivated our work. We also show by using several random instances that our methods improve the previous results. |
| Researcher Affiliation | Academia | Guillaume Perez and Jean-Charles R egin Universit e Nice Sophia Antipolis, CNRS, I3S, France EMAIL, EMAIL |
| Pseudocode | No | The paper does not include any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access information (e.g., repository links, explicit statements of code release) for the source code of the methodology described. |
| Open Datasets | No | The paper mentions using "The fables of Jean de La Fontaine" and "random instances" but does not provide concrete access information (link, DOI, repository, or formal citation with author/year) for these datasets, nor does it specify their public availability. |
| Dataset Splits | No | The paper does not provide specific details on dataset splits (e.g., percentages, sample counts, or citations to predefined splits) for training, validation, or testing. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, processor types, memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper mentions "constraint programming solvers" but does not provide specific software names with version numbers (e.g., library or solver names with their corresponding version numbers) used in the experiments. |
| Experiment Setup | Yes | We consider the problem detailed in Section Motivation. [...] For the experimentation, we used "The fables of Jean de La Fontaine". [...] We have a constraint of arity 18 and an all Different constraint. [...] We select randomly a certain number of tuples and build an MDD from this tuple set. We associate each arc with a random cost between 0 and 10. [...] Table 1: Times needed to build the sequences with minimum of violations (Time out 1800s). [...] Table 3: search for the best solution (construction time is included, arity 18, domain size 18). |