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..
On the Pursuit of EFX for Chores: Non-existence and Approximations
Authors: Vasilis Christoforidis, Christodoulos Santorinaios
IJCAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We resolve this question by providing a negative answer for the latter, presenting a simple construction that admits no EFX solutions for allocating six items to three agents equipped with superadditive cost functions, thus proving a separation result between goods and bads. In fact, we uncover a deeper insight, showing that the instance has unbounded approximation ratio. Moreover, we show that deciding whether an EFX allocation exists is NP-complete. On the positive side, we establish the existence of EFX allocations under general monotone cost functions when the number of items is at most n+2. We then shift our attention to additive cost functions. We employ a general framework in order to improve the approximation guarantees in the well-studied case of three additive agents, and provide several conditional approximation bounds that leverage ordinal information. |
| Researcher Affiliation | Academia | Vasilis Christoforidis1,2 and Christodoulos Santorinaios1,3 1Archimedes / Athena RC 2Aristotle University of Thessaloniki 3Athens University of Economics and Business |
| Pseudocode | Yes | Algorithm 1 Top trading envy cycle elimination algorithm, Algorithm 2 Chore approximation framework, Algorithm 3 Top n 1 disagreement |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described in this paper. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments on datasets, thus no information on publicly available datasets is provided. |
| Dataset Splits | No | The paper is theoretical and does not describe empirical experiments with data splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require specific hardware, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers that would be needed to replicate experiments. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |