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 [1].
Deep Supervised Hashing with Nonlinear Projections
Authors: Sen Su, Gang Chen, Xiang Cheng, Rong Bi
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The provided text only contains the paper title and conference information, without any content describing research methodology, experiments, or results. Therefore, it is impossible to determine if the research is experimental or theoretical. |
| Researcher Affiliation | Academia | The provided text only contains the paper title and conference information, without any author affiliations or email domains. Therefore, it is impossible to classify the author affiliation types. |
| Pseudocode | No | The provided text only contains the paper title and conference information, without any content including pseudocode or algorithm blocks. Therefore, it is impossible to determine if pseudocode is present. |
| Open Source Code | No | The provided text only contains the paper title and conference information, without any content providing concrete access to source code. Therefore, it is impossible to determine if open-source code is provided. |
| Open Datasets | No | The provided text only contains the paper title and conference information, without any content describing datasets or their access information. Therefore, it is impossible to determine if training data access is provided. |
| Dataset Splits | No | The provided text only contains the paper title and conference information, without any content describing dataset split information for validation. Therefore, it is impossible to determine if validation split information is provided. |
| Hardware Specification | No | The provided text only contains the paper title and conference information, without any content describing hardware specifications. Therefore, it is impossible to determine if hardware specifications are provided. |
| Software Dependencies | No | The provided text only contains the paper title and conference information, without any content describing software dependencies. Therefore, it is impossible to determine if software dependencies are provided. |
| Experiment Setup | No | The provided text only contains the paper title and conference information, without any content describing the experimental setup. Therefore, it is impossible to determine if experiment setup details are provided. |