Compile!
Authors: Pierre Marquis
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This paper is concerned with knowledge compilation (KC), a family of approaches developed in AI for more than twenty years. ... The three topics, as well as an overview of the main results from the literature, are presented. Some recent research lines are also discussed. |
| Researcher Affiliation | Academia | Pierre Marquis CRIL-CNRS, Universit e d Artois, France marquis@cril.univ-artois.fr |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions that external compilers are 'available on the Web' but does not provide concrete access to source code for the methodology or work described within this specific paper. |
| Open Datasets | No | The paper does not provide concrete access information (specific link, DOI, repository name, formal citation with authors/year, or reference to established benchmark datasets) for a publicly available or open dataset used in its own experiments. It refers to instances compiled by external tools. |
| Dataset Splits | No | The paper does not report on new experiments conducted by the author, thus no specific dataset split information for validation is provided. |
| Hardware Specification | No | The paper mentions performance times for external compilers but does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) for any experiments. |
| Software Dependencies | No | The paper refers to various software tools but does not provide specific ancillary software details (e.g., library or solver names with version numbers) needed to replicate any experiments it describes. |
| Experiment Setup | No | The paper does not report on new experiments conducted by the author, thus no specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) are provided. |