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..
Robustness-Guided Image Synthesis for Data-Free Quantization
Authors: Jianhong Bai, Yuchen Yang, Huanpeng Chu, Hualiang Wang, Zuozhu Liu, Ruizhe Chen, Xiaoxuan He, Lianrui Mu, Chengfei Cai, Haoji Hu
AAAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct extensive experiments, showing that the proposed RIS outperforms various existing data-free quantization methods by a large margin, and can be further extended to data-free knowledge distillation. |
| Researcher Affiliation | Collaboration | 1Zhejiang University 2Kuaishou Technology 3The Hong Kong University of Science and Technology 4Tencent Data Platform |
| Pseudocode | Yes | Algorithm 1: The synthesis process of our RIS scheme. |
| Open Source Code | No | The paper does not provide an explicit statement or link for open-source code for the described methodology. |
| Open Datasets | Yes | We evaluated the proposed RIS on CIFAR-10/100 (Krizhevsky, Hinton et al. 2009) and Image Net (Krizhevsky, Sutskever, and Hinton 2012). |
| Dataset Splits | No | The paper refers to standard datasets (CIFAR-10/100, ImageNet) but does not explicitly provide specific training/test/validation split percentages, sample counts, or explicit instructions for reproducing the data partitioning in the provided text. |
| Hardware Specification | No | No specific hardware details (GPU/CPU models, memory, or detailed computer specifications) used for running experiments were provided. |
| Software Dependencies | No | No specific software dependencies with version numbers were mentioned in the paper. |
| Experiment Setup | Yes | More training details can be found in Appendix D. |