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..
Deep Multimodal Hashing with Orthogonal Regularization
Authors: Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Comprehensive experiments on WIKI and NUS-WIDE, demonstrate a substantial gain of DMHOR compared with state-of-the-art methods. |
| Researcher Affiliation | Academia | 1Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology, Tsinghua University. Beijing, China |
| Pseudocode | Yes | Algorithm 1 Fine-tuning for DMHOR |
| Open Source Code | No | The paper does not provide any specific links or explicit statements about the availability of open-source code for the described methodology. |
| Open Datasets | Yes | NUS-WIDE [Chua et al., 2009] is a public web image dataset [...] WIKI [Rasiwasia et al., 2010] is a web document dataset |
| Dataset Splits | No | The paper specifies training and test sets but does not explicitly mention a separate validation set with specific split information. |
| Hardware Specification | Yes | We run the following experiments with implementation in Matlab on a machine running Windows Server 2008 with 12 2.39GHz cores and 192 GB of memory. |
| Software Dependencies | No | The paper mentions "implementation in Matlab" but does not specify any version numbers for Matlab or any other software libraries or dependencies. |
| Experiment Setup | Yes | The hyper-parameters of ฮป, ยต and ฮฝ are set as 0.5, 0.5 and 0.001 by using grid search. |