Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
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.
A Differentially Private Linear-Time fPTAS for the Minimum Enclosing Ball Problem
Authors: Bar Mahpud, Or Sheffet
NeurIPS 2022 | Venue PDF | LLM Run Details | Input Tokens: 19,111 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,798 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Lastly, we test our algorithm empirically and discuss open problems. |
| Researcher Affiliation | Academia | Bar Mahpud Or Sheffet Faculty of Engineering Bar-Ilan University, Israel EMAIL |
| Pseudocode | Yes | Algorithm 1 Non-Private Minimum Enclosing Ball |
| Open Source Code | Yes | Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [Yes] In the Supplementary Material |
| Open Datasets | Yes | Dataset available freely on archive.ics.uci.edu/ml/datasets/ Bar+Crawl%3A+Detecting+Heavy+Drinking. |
| Dataset Splits | No | Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [N/A] |
| Hardware Specification | No | The paper states that the total amount of compute and type of resources used were included ([Yes] in self-evaluation), but these specific details are not present in the provided main paper text to be quoted. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | No | Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? [N/A] |