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.
Private Set Union with Multiple Contributions
Authors: Travis Dick, Haim Kaplan, Alex Kulesza, Uri Stemmer, Ziteng Sun, Ananda Theertha Suresh
NeurIPS 2025 | Venue PDF | LLM Run Details | Input Tokens: 37,690 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 2,102 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Justification: The paper does not include experiments. |
| Researcher Affiliation | Collaboration | Travis Dick Google Research Haim Kaplan Tel Aviv University and Google Research Alex Kulesza Google Research Uri Stemmer Tel Aviv University and Google Research Ziteng Sun Google Research Ananda Theertha Suresh Google Research |
| Pseudocode | Yes | Algorithm 1 Bicrit Notation: Let k denote the contribution bound, let X be a domain of items, and let X,k = {B X : |B| k} denote the set of all possible bags of size at most k from X. Input: Dataset D ( X,k)n containing n bags, privacy parameters ε, δ > 0. |
| Open Source Code | No | Justification: The paper does not include experiments requiring code. |
| Open Datasets | No | Justification: The paper does not include experiments. |
| Dataset Splits | No | Justification: The paper does not include experiments. |
| Hardware Specification | No | Justification: The paper does not include experiments. |
| Software Dependencies | No | Justification: The paper does not include experiments. |
| Experiment Setup | No | Justification: The paper does not include experiments. |