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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Making Pairwise Binary Graphical Models Attractive
Authors: Nicholas Ruozzi, Tony Jebara
NeurIPS 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We illustrate the theory through a series of experiments on small models, grid graphs, and vertex induced subgraphs of the Epinions social network |
| Researcher Affiliation | Academia | Nicholas Ruozzi Institute for Data Sciences and Engineering Columbia University New York, NY 10027 EMAIL Tony Jebara Department of Computer Science Columbia University New York, NY 10027 EMAIL |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link for open-source code availability. |
| Open Datasets | No | The paper mentions the 'Epinions social network' in a footnote but does not provide specific access information (link, DOI, or formal citation with authors/year) for the dataset itself. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, or citations to predefined splits) needed for data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types, or memory) used for running experiments. |
| Software Dependencies | No | The paper mentions a 'standard implementation of reweighted, asynchronous message passing' but does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | We test the performance of these algorithms on Ising models with a randomly selected external ๏ฌeld and various interaction strengths on the edges. ... The algorithms were run until the messages in consecutive time steps differed by less than 10 8 or until more than 20, 000 iterations were performed (a single iteration consists of updating all of the messages in the model). |