What Is Hot in CHI
Authors: Wei Li
AAAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Here, I would like to introduce progress in HCI research which will bring new opportunities and challenges to AI community. |
| Researcher Affiliation | Industry | Autodesk Research, Toronto, Canada wei.li@autodesk.com |
| Pseudocode | No | No pseudocode or algorithm blocks are present in the paper. |
| Open Source Code | No | The paper refers to an external project link: '1 www.autodeskresearch.com/paperforager' for 'Project Paperforager', but this is not a statement that the methodology described in this survey paper has open-source code. The paper itself does not present a novel methodology. |
| Open Datasets | No | The paper does not mention using any dataset for training conducted by the authors, nor does it provide concrete access information (link, DOI, formal citation) for any publicly available dataset that the authors might have used in their work. |
| Dataset Splits | No | The paper does not describe any experiments conducted by the authors, and therefore, no specific dataset split information for validation is provided. |
| Hardware Specification | No | No specific hardware details (like GPU/CPU models, memory, or specific computer specifications) used for running experiments are mentioned in the paper. The paper discusses types of devices in general, but not the hardware used by the authors for their research. |
| Software Dependencies | No | No specific ancillary software details with version numbers (e.g., library or solver names with versions) are provided for replicating any work or experiments described in the paper. |
| Experiment Setup | No | The paper does not describe any experiments conducted by the authors, and therefore, no specific experimental setup details (like hyperparameters or training configurations) are provided. |