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..
Redividing the Cake
Authors: Erel Segal-Halevi
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We present re-division protocols that attain various trade-off points between fairness and ownership rights, in various settings differing in the geometric constraints on the allotments: (a) no geometric constraints; (b) connectivity the cake is a one-dimensional interval and each piece must be a contiguous interval; (c) rectangularity the cake is a two-dimensional rectangle and the pieces should be rectangles; (d) convexity the cake is a two-dimensional convex polygon and the pieces should be convex. |
| Researcher Affiliation | Academia | Erel Segal-Halevi Ariel University, Ariel 40700, Israel EMAIL |
| Pseudocode | Yes | Proof. Let r = p/q with p < q some positive integers. For every pair of agents i, j (including i = j), the protocol does: Step 1. Agent i divides Zi Yj to q equal-value pieces. Step 2. Agent j takes the p best pieces in its eyes. Step 3. Agent i takes the remaining q p pieces. |
| Open Source Code | No | The paper does not provide any statement or link indicating the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not conduct empirical studies using datasets. |
| Dataset Splits | No | The paper is theoretical and does not conduct empirical studies that would involve training/test/validation dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not conduct empirical experiments, therefore no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with specific hyperparameters or training configurations. |