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..
Learning User Perceived Clusters with Feature-Level Supervision
Authors: Ting-Yu Cheng, Guiguan Lin, xinyang gong, Kang-Jun Liu, Shan-Hung (Brandon) Wu
NeurIPS 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The figures display performance comparisons of different methods like OKM, OKM*, OKM*+LPE, and OKM*+NPE with y-axis values ranging from 0 to 1. This implies empirical evaluation and data analysis. |
| Researcher Affiliation | Academia | No author affiliations, university names, company names, or email domains are provided in the given text snippet. |
| Pseudocode | No | No structured pseudocode or algorithm blocks are present in the provided text. |
| Open Source Code | No | No concrete access information (specific repository link, explicit code release statement, or code in supplementary materials) for source code is provided in the text. |
| Open Datasets | No | No concrete access information (specific link, DOI, repository name, formal citation, or reference to established benchmark datasets) for a publicly available dataset is provided in the text. |
| Dataset Splits | No | No specific dataset split information (percentages, sample counts, citations to predefined splits, or detailed splitting methodology) is provided in the text. |
| Hardware Specification | No | No specific hardware details (exact GPU/CPU models, processor types, memory amounts, or detailed computer specifications) used for running experiments are provided in the text. |
| Software Dependencies | No | No specific ancillary software details (library or solver names with version numbers) needed to replicate the experiment are provided in the text. |
| Experiment Setup | No | No specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) are provided in the text. |