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 [1].
A Little Subsidy Ensures MMS Allocation for Three Agents
Authors: Xiaowei Wu, Quan Xue, Shengwei Zhou
IJCAI 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our work focuses on the case of three agents. Assuming that the maximum cost/utility of an item to an agent can be compensated by one dollar, we demonstrate that a total subsidy of 1/6 dollars is sufficient to ensure the existence of Maximin Share (MMS) allocations for both goods and chores. Additionally, we establish lower bounds of the required subsidies. |
| Researcher Affiliation | Academia | Xiaowei Wu1 , Quan Xue2 , Shengwei Zhou1 1 IOTSC, University of Macau 2 University of Hong Kong EMAIL, EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: Load-Balancing(M , n , c) |
| Open Source Code | Yes | We provide the complete code of our LP in Supplementary Material. Our LP generates an instance for which any allocation requires a total subsidy of at least 2/49. For ease of presentation, in the following, we present the scaled instance in which the (minimum) required subsidy is exactly 1. ... We provide the complete code for verification in Supplementary Material. |
| Open Datasets | No | The paper does not use a publicly available dataset for empirical evaluation. It constructs a specific theoretical instance for its analysis, as described in Section 3.4: "Consider the following instance with 3 agents and 9 items." |
| Dataset Splits | No | The paper does not conduct empirical experiments on a dataset that would require training/test/validation splits. The instances discussed are theoretical constructions for proofs and counterexamples. |
| Hardware Specification | No | The paper is theoretical and does not describe experimental evaluation that would involve specific hardware. The computational aspects (LP, verification code) do not include hardware specifications. |
| Software Dependencies | No | The paper mentions using an "LP" (Linear Program) to generate instances, but does not specify any particular solver or software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and focuses on mathematical proofs and the existence of allocations, rather than empirical experiments with specific setup details like hyperparameters or training configurations. |