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..
Enabling Knowledge Refinement upon New Concepts in Abductive Learning
Authors: Yu-Xuan Huang, Wang-Zhou Dai, Yuan Jiang, Zhi-Hua Zhou
AAAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on three neuro-symbolic learning tasks verified the effectiveness of the proposed approach. All experiments are repeated ten times on a server with Intel Xeon Gold 6242R CPU and Nvidia RTX 3090 GPU. |
| Researcher Affiliation | Academia | National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China EMAIL |
| Pseudocode | Yes | Algorithm 1 ABLnc; Algorithm 2 Conflict Resolution; Algorithm 3 Matching Knowledge Graph |
| Open Source Code | Yes | The code is available for download1. 1https://github.com/AbductiveLearning/ABLnc |
| Open Datasets | Yes | The dataset consists of 10k pairs of images, where the digits are randomly generated and their images are randomly sampled from the training set of MNIST. |
| Dataset Splits | Yes | The hyperparameters of ABLnc are determined by cross-validation on training data. |
| Hardware Specification | Yes | All experiments are repeated ten times on a server with Intel Xeon Gold 6242R CPU and Nvidia RTX 3090 GPU. |
| Software Dependencies | No | The paper mentions software components such as CNN, LOF, ASP, ILASP, and Transformer, but does not provide specific version numbers for any of these dependencies. |
| Experiment Setup | No | The paper mentions that 'The hyperparameters of ABLnc are determined by cross-validation on training data' but does not provide specific values for these hyperparameters, training configurations, or other system-level settings. |