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..
DPSampler: Exact Weighted Sampling Using Dynamic Programming
Authors: Jeffrey M. Dudek, Aditya A. Shrotri, Moshe Y. Vardi
IJCAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 6 Empirical Evaluation We seek to answer the following questions in our study: 1. How close is the distribution generated by DPSampler to that of an ideal sampler? 2. How does the new top-down ADD-sampling algorithm (Alg. 1) perform compared to the bottom-up procedure of [Chakraborty et al., 2020]? 3. How does DPSampler perform compared to the state-of-the-art, especially on low-treewidth instances? |
| Researcher Affiliation | Academia | Jeffrey M. Dudek , Aditya A. Shrotri , Moshe Y. Vardi Rice University EMAIL |
| Pseudocode | Yes | Algorithm 1 sample From ADD(f, w, σ) |
| Open Source Code | Yes | Code, results and full version of the text is available at https: //www.gitlab.com/Shrotri/dpsampler |
| Open Datasets | Yes | We tested the two implementations on the suite of 1945 benchmarks used in [Dudek et al., 2020b] |
| Dataset Splits | No | The paper uses pre-existing benchmark sets and does not describe explicit training, validation, or test dataset splits as commonly found in machine learning experiments. |
| Hardware Specification | Yes | Each experiment had exclusive access to one node comprising of 16 cores (32 threads) with an Intel Xeon E5-2650 v2 processor running at 2.6 GHz, with memory capped at 30 GB. |
| Software Dependencies | Yes | We used GCC 9.4.0 for compiling DPSampler with Ofast flag enabled, along with CUDD [Somenzi, 2012] library version 3.0. |
| Experiment Setup | Yes | A benchmark is solved by a tool if the tool is able to generate 5000 samples within a timeout of 1000 seconds. We treat both timeouts and memouts as failures. |