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..
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Authors: Halvard Hummel
IJCAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We prove that for any integer c > 0, there exists a number of agents nc such that an MMS allocation exists for any instance with n nc agents and at most n + c items, where nc 0.6597c c! for allocation of goods and nc 0.7838c c! for chores. Furthermore, we show that for n = 3 agents, all instances with n + 6 goods have an MMS allocation. Our proofs of Theorems 1 and 3 build on two new structural properties of ordered instances. |
| Researcher Affiliation | Academia | Halvard Hummel Norwegian University of Science and Technology 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 regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | This is a theoretical paper and does not involve experiments with datasets. |
| Dataset Splits | No | This is a theoretical paper and does not involve experiments with dataset splits. |
| Hardware Specification | No | This is a theoretical paper and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | This is a theoretical paper and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not describe any experimental setup details such as hyperparameters or training settings. |