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..
Non-monotone Sequential Submodular Maximization
Authors: Shaojie Tang, Jing Yuan
AAAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The empirical evaluations further validate the effectiveness of our proposed algorithms in the domain of video recommendations. |
| Researcher Affiliation | Academia | 1Naveen Jindal School of Management, University of Texas at Dallas 2 Department of Computer Science and Engineering, University of North Texas |
| Pseudocode | Yes | Algorithm 1: Sampling-Greedy |
| Open Source Code | No | No explicit statement or link providing access to the source code for the methodology was found. |
| Open Datasets | Yes | We evaluate our algorithms and benchmarks on the latest Movie Lens dataset (Harper and Konstan 2015), consisting of 62, 423 movies, of which 13, 816 have both user-generated tags and ratings. |
| Dataset Splits | No | The paper describes the dataset used but does not provide specific details on training, validation, or test dataset splits. |
| Hardware Specification | No | No specific hardware details (like GPU/CPU models or cloud instances) used for running experiments were mentioned in the paper. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., Python, PyTorch, or other libraries with their versions). |
| Experiment Setup | Yes | We set η = 35 and adjust the parameters α and β to ensure that the two components in fj( ) are roughly equal in magnitude. In each experimental set, we perform 100 rounds and present the average results as follows. |