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..
Action2Activity: Recognizing Complex Activities from Sensor Data
Authors: Ye Liu, Liqiang Nie, Lei Han, Luming Zhang, David S. Rosenblum
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on a real-world dataset demonstrate the effectiveness of our work. |
| Researcher Affiliation | Academia | School of Computing, National University of Singapore Department of Computer Science, Hong Kong Baptist University |
| Pseudocode | No | The paper describes algorithms textually and mathematically but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions using LIBSVM and OpenCV, providing links to these third-party libraries, but does not state that the authors' own implementation code for the described methodology is publicly available. |
| Open Datasets | Yes | The Opportunity dataset [Chavarriaga et al., 2013] |
| Dataset Splits | Yes | The performance reported in this paper was measured based on 10-fold cross-validation classification accuracy. |
| Hardware Specification | No | The paper does not specify the hardware (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | We implemented this method with the help of LIBSVM2. We selected a linear kernel. ... We employed the k-Nearest Neighbors in Open CV3 and set K = 7. |
| Experiment Setup | Yes | For a MTL, we set minsup = 0.01 and twin = 2 Lavg over all the experiments, where Lavg is the average length of action intervals in an activity. ... We initially fixed λ and θ, and then varied γ from 0.001 to 5 and doubled the value at each step. ... We then set γ = 0.001, θ = 1 and varied λ. ... Finally, we set γ = 0.001, λ = 0.05 and varied θ. |