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].
Participatory Budgeting with Project Interactions
Authors: Pallavi Jain, Krzysztof Sornat, Nimrod Talmon
IJCAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study the computational complexity of finding bundles that maximize voter utility, as defined with respect to such functions. Motivated by the desire to incorporate project interactions in real-world participatory budgeting systems, we identify certain cases that admit efficient aggregation in the presence of such project interactions.We study the possibility of identifying bundles maximizing total utility for various interaction functions. In Section 3, we show general intractability. Then, to better understand the combinatorics of our problems and to identify special cases admitting efficient algorithms, we proceed in 2 directions: In Section 4 we study the parameterized complexity of our problems wrt. problem parameters that might be small in real-world instances; and in Section 5 we study the complexity of our problems for instances of two domain restrictions suited for our setting. |
| Researcher Affiliation | Academia | Pallavi Jain , Krzysztof Sornat and Nimrod Talmon Ben-Gurion University, Israel EMAIL, EMAIL |
| Pseudocode | No | The paper describes algorithms through prose and mathematical equations (e.g., "We define the dynamic programming table as follows:", "T[i, j] = min S zi: u S j {T[i 1, j u S] + cost(S)}"), but it does not present them in a structured pseudocode or algorithm block. |
| Open Source Code | No | The paper does not contain any statement about making its source code openly available or provide a link to a code repository. |
| Open Datasets | No | This is a theoretical paper that does not conduct experiments involving datasets, training, or evaluation. The "Example 1" section is purely illustrative and does not refer to a publicly available dataset. |
| Dataset Splits | No | This is a theoretical paper that does not conduct experiments, and thus does not define dataset splits for validation. |
| Hardware Specification | No | This is a theoretical paper that does not describe computational experiments and therefore does not specify any hardware used. |
| Software Dependencies | No | The paper is theoretical and does not describe software implementations or experiments, so it does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper and does not include any description of an experimental setup or hyperparameters. |