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..
New Algorithms for Japanese Residency Matching
Authors: Zhaohong Sun, Taiki Todo, Makoto Yokoo
IJCAI 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this section, we empirically evaluate our newly designed algorithms GDA-RH and GDA-RO. and Figure 2: Comparison of three algorithms in terms of doctors welfare |
| Researcher Affiliation | Academia | Zhaohong Sun1 , Taiki Todo2 and Makoto Yokoo2 1UNSW Sydney 2Kyushu University |
| Pseudocode | Yes | Algorithm 1 Generalized Deferred Acceptance with Regions, Algorithm 2 Choice function Chr of region r, Algorithm 3 Choice function Chh of hospital h |
| Open Source Code | No | The paper does not provide an explicit statement or a link to open-source code for the described methodology. |
| Open Datasets | No | The preference proļ¬les of the doctors and the priority proļ¬les of the hospitals and regions are generated by Mallows Model (MM), which is commonly used to generate preference and priority proļ¬les when such information is unavailable [Lu and Boutilier, 2011]. We exploit the Pref Lib library to generate preference and priority proļ¬les [Mattei and Walsh, 2013]. |
| Dataset Splits | No | The paper does not explicitly state training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide any specific hardware details used for running the experiments. |
| Software Dependencies | No | We exploit the Pref Lib library to generate preference and priority proļ¬les [Mattei and Walsh, 2013]. |
| Experiment Setup | Yes | We consider a medium-sized market with |D| = 200 doctors, |H| = 10 hospitals, and |R| = 2 regions. We assume all hospitals have the same capacity and artiļ¬cial-cap, and all regions have the same number of hospitals and regional quotas. ... The artiļ¬cial cap is set to |D| / |H| ā 1.1 = 22, and the regional quota is set to |D| / |R| ā 1.1 = 110 ... a ratio is chosen from three reasonable values: {1.2, 1.5, 2.0}. ... In this experiment, Īø takes three values from {0.2, 0.5, 0.8}. |