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..
Assignments for Congestion-Averse Agents: Seeking Competitive and Envy-Free Solutions
Authors: Jiehua Chen, Jiong Guo, Yinghui Wen
NeurIPS 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The model studied in our paper is a theoretical and abstract model. Our analysis is based on worst case analysis. There are no experiments. |
| Researcher Affiliation | Academia | Jiehua Chen Institute of Logic and Computation TU Wien Austria EMAIL Jiong Guo School of Computer Science and Technology Shandong University Qingdao, China EMAIL Yinghui Wen Digital and Intelligent Center Shandong Institute of Information Technology Industry Development Jinan, China EMAIL |
| Pseudocode | Yes | ALGORITHM 1: Determining the existence of CP assignments |
| Open Source Code | No | Answer: [NA] Justification: As mentioned, there are no experiments. But all stated results are proved in the main part or appendix. |
| Open Datasets | No | Answer: [NA] Justification: As mentioned, there are no experiments. |
| Dataset Splits | No | Answer: [NA] Justification: As mentioned, there are no experiments. |
| Hardware Specification | No | Answer: [NA] Justification: As mentioned, there are no experiments. |
| Software Dependencies | No | Answer: [NA] Justification: As mentioned, there are no experiments. |
| Experiment Setup | No | Answer: [NA] Justification: As mentioned, there are no experiments. |