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.
Randomized Truthful Auctions with Learning Agents
Authors: Gagan Aggarwal, Anupam Gupta, Andres Perlroth, Grigoris Velegkas
NeurIPS 2024 | Venue PDF | LLM Run Details | Input Tokens: 32,571 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,585 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 | The answer NA means that the paper does not include experiments. |
| Researcher Affiliation | Collaboration | Gagan Aggarwal Google Research EMAIL Anupam Gupta New York University, Google Research EMAIL Andres Perlroth Google Research EMAIL Grigoris Velegkas Yale University EMAIL |
| Pseudocode | Yes | ALGORITHM 1: Multiplicative Weights Update Algorithm. |
| Open Source Code | No | The answer NA means that paper does not include experiments requiring code. |
| Open Datasets | No | The paper does not include experiments or use datasets for training. |
| Dataset Splits | No | The paper does not include experiments or specify dataset splits for validation. |
| Hardware Specification | No | The paper does not include experiments and therefore does not provide hardware specifications. |
| Software Dependencies | No | The paper does not include experiments and therefore does not provide specific software dependencies with version numbers for replication. |
| Experiment Setup | No | The paper does not include experiments and therefore does not provide specific experimental setup details like hyperparameters. |