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..
ST-MVL: Filling Missing Values in Geo-Sensory Time Series Data
Authors: Xiuwen Yi, Yu Zheng, Junbo Zhang, Tianrui Li
IJCAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our method based on Beijing air quality and meteorological data, finding advantages to our model compared with ten baseline approaches. |
| Researcher Affiliation | Collaboration | 1School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China 2Microsoft Research, Beijing, China 3Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences |
| Pseudocode | Yes | Algorithm 1 ST-MVL Input: Original Data Matrix 𝑀, 𝜔, 𝛼, 𝛽; Output: Final Data Matrix; |
| Open Source Code | Yes | The code and datasets have been released at: http://research.microsoft.com/apps/pubs/?id=264768. |
| Open Datasets | Yes | We evaluate our model based on two real datasets: air quality and meteorological data in Beijing from 2014/05/01 to 2015/04/30 [Zheng et al., 2015] |
| Dataset Splits | No | We partition the 1-year data into two parts, using the 3rd, 6th, 9th and 12th months as a test set and the rest for a training set. The paper does not mention a distinct validation set. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used for experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers. |
| Experiment Setup | Yes | Parameter Settings: We test different 𝛼 for IDW, 𝛽 for SES, and 𝜔 for UCF & ICF, finding a best setting for them, e.g. when 𝛼=4, 𝛽=0.85, and 𝜔=7 achieve the best performance in PM2.5 property. |