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..
Fair Knapsack
Authors: Till Fluschnik, Piotr Skowron, Mervin Triphaus, Kai Wilker1941-1948
AAAI 2019 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our complexity results are outlined in Table 1. In summary, we showed that computing an individually best or a diverse knapsack can be done efficiently under some constraints. On the contrary, we give multiple evidences that computing a fair knapsack is computationally hard. |
| Researcher Affiliation | Academia | 1Algorithmics and Computational Complexity, Faculty IV, TU Berlin, Berlin, Germany till.fluschnik@tu-berlin.de, EMAIL 2Faculty of Mathematics, Informatics, and Mechanics, University of Warsaw, Warsaw, Poland EMAIL |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not discuss datasets or their public availability. |
| Dataset Splits | No | The paper is theoretical and does not describe dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not mention any hardware specifications used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details or hyperparameters. |