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 Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
Authors: Huikang Liu, Xiao Li, Anthony Man-Cho So
NeurIPS 2023 | Venue PDF | LLM Run Details | Input Tokens: 27,196 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 6,613 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 | Experiment results demonstrate the effectiveness of Re Sync. |
| Researcher Affiliation | Academia | Huikang Liu School of Information Management and Engineering Shanghai University of Finance and Economics EMAIL; Xiao Li School of Data Science The Chinese University of Hong Kong, Shenzhen EMAIL; Anthony Man-Cho So Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong EMAIL |
| Pseudocode | Yes | Algorithm 1 Re Sync: Riemannian Subgradient Synchronization; Algorithm 2 Spectr In: Spectral Initialization |
| Open Source Code | Yes | Our code is available at https://github.com/Huikang2019/Re Sync. |
| Open Datasets | Yes | We consider the global alignment problem of three-dimensional scans from the Lucy dataset, which is a down-sampled version of the dataset containing 368 scans with a total number of 3.5 million triangles. We refer to [39] for more details about the experiment setting. |
| Dataset Splits | No | The paper describes data generation for synthetic data and the use of the Lucy dataset, but does not specify explicit train/validation/test splits (e.g., percentages, sample counts, or predefined splits) for reproducibility. |
| Hardware Specification | Yes | Our experiments are conducted on a personal computer with a 2.90GHz 8-core CPU and 32GB memory. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers for its implementation or experiments. |
| Experiment Setup | Yes | We use the initial step size ยต0 = 1/npq and the decaying factor ฮณ {0.7, 0.8, 0.85, 0.90, 0.95, 0.98} in Re Sync. |