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..
SpFormer: Spatio-Temporal Modeling for Scanpaths with Transformer
Authors: Wenqi Zhong, Linzhi Yu, Chen Xia, Junwei Han, Dingwen Zhang
AAAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct extensive experiments on four databases under three tasks. |
| Researcher Affiliation | Academia | School of Automation, Northwestern Polytechnical University, China EMAIL, EMAIL, EMAIL, EMAIL, EMAIL |
| Pseudocode | No | The paper describes methods using text and mathematical equations, but does not include any explicitly labeled 'Pseudocode' or 'Algorithm' blocks. |
| Open Source Code | Yes | The code can be obtained from https://github.com/wenqizhong/Sp Former. |
| Open Datasets | Yes | We apply two datasets, Saliency4ASD (Duan et al. 2019) dataset and our collected dataset, to evaluate the ASD recognition performance of the Sp Former. ... We utilize a toddler age prediction (TAP) dataset1 obtained from (Dalrymple et al. 2019)... 1https://osf.io/ugvj4 ... Koehler et al. (2014) proposed a visual perceptual task (VPT) dataset2... 2https://data.mendeley.com/datasets/8rj98pp6km/1 |
| Dataset Splits | No | The paper states 'Utrain denotes the subject set for training' and refers to previous experimental protocols for settings, but does not provide specific numerical train/validation/test dataset splits within the provided text. |
| Hardware Specification | No | The paper does not provide any specific hardware specifications such as GPU models, CPU types, or memory used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies or their version numbers (e.g., Python, PyTorch, or CUDA versions) required for replication. |
| Experiment Setup | Yes | We set α = σ = 0.5, β = 1 σ = 0.5 in Eq. (20), and λ = 0.1 in Eq.( 24). |