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].
Robust Market Equilibria with Uncertain Preferences
Authors: Riley Murray, Christian Kroer, Alex Peysakhovich, Parikshit Shah2192-2199
AAAI 2020 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 5 Experimental Results |
| Researcher Affiliation | Collaboration | 1Facebook Core Data Science, 2Facebook Arti๏ฌcial Intelligence Research 3California Institute of Technology, 4Columbia University |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described in this paper. |
| Open Datasets | Yes | We start with the Movie Lens 1M dataset where 6000 individuals give ratings to 4000 movies. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | Yes | For our implementation we rely on CVXPY 1.0 (Diamond and Boyd 2016; Agrawal et al. 2018) to interface with solvers MOSEK (Mosek 2010; Dahl and Andersen 2019) and ECOS (Domahidi, Chu, and Boyd 2013). |
| Experiment Setup | Yes | Experiments here use the 2-norm; refer to supplementary material for the same experiments under 1-norm uncertainty. For our implementation we rely on CVXPY 1.0 (Diamond and Boyd 2016; Agrawal et al. 2018) to interface with solvers MOSEK (Mosek 2010; Dahl and Andersen 2019) and ECOS (Domahidi, Chu, and Boyd 2013). |