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..
Greedy Approximation Algorithms for Active Sequential Hypothesis Testing
Authors: Kyra Gan, Su Jia, Andrew Li
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We numerically evaluate the performance of our algorithms using both synthetic and real-world DNA mutation data, demonstrating that our algorithms outperform previously proposed heuristic policies by large margins. |
| Researcher Affiliation | Academia | Kyra Gan , Su Jia , Andrew A. Li Carnegie Mellon University Pittsburgh, PA 15213 EMAIL |
| Pseudocode | Yes | Algorithm 1 Partially Adaptive Algorithm: Rn B(B, ) |
| Open Source Code | No | The paper does not provide any explicit statement about open-sourcing its code or a link to a code repository for its methodology. |
| Open Datasets | Yes | We use genetic mutation data from real cancer patients: the publicly-available catalogue of somatic mutations in cancer (COSMIC) [40, 16], which includes the de-identi๏ฌed gene-screening panels for 1,350,015 patients. |
| Dataset Splits | No | The paper describes the number of instances and replications for synthetic data, and the processing of real-world data, but does not provide specific train, validation, or test dataset splits in terms of percentages or sample counts. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware (e.g., GPU/CPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers used for the experiments. |
| Experiment Setup | Yes | The threshold for entering Phase 2 policy in NJ Adaptive was set to be 0.1. [...] The threshold for entering Phase 2 policy, r, in NJ Adaptive was set to be 0.3. |