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..
HiHPQ: Hierarchical Hyperbolic Product Quantization for Unsupervised Image Retrieval
Authors: Zexuan Qiu, Jiahong Liu, Yankai Chen, Irwin King
AAAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on benchmarks show that our proposed method outperforms state-of-the-art baselines. |
| Researcher Affiliation | Academia | Zexuan Qiu, Jiahong Liu, Yankai Chen, Irwin King The Chinese University of Hong Kong EMAIL |
| Pseudocode | No | The paper does not contain any pseudocode or explicitly labeled algorithm blocks. |
| Open Source Code | No | The paper does not include an unambiguous statement about releasing source code for the methodology described, nor does it provide a direct link to a code repository. |
| Open Datasets | Yes | The proposed method is evaluated using Flickr25K (Huiskes and Lew 2008), NUS-WIDE (Chua et al. 2009), as well as two experimental protocols CIFAR10 (I) and CIFAR-10 (II) both of which are based on CIFAR-10 (Krizhevsky, Hinton et al. 2009). |
| Dataset Splits | No | The paper mentions using CIFAR-10, Flickr25K, and NUS-WIDE datasets but does not explicitly state the specific training, validation, and test splits (percentages, counts, or specific predefined split references) used for the experiments. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | The pre-defined hierarchies for different datasets are: [50, 20] on Flickr25K; [200, 100, 50] on CIFAR-10 (I); [100, 50, 25] on CIFAR-10 (II); [200, 100, 75] on NUSWIDE. Please refer to the supplementary material for more implementation details. |