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..
DeepPSL: End-to-End Perception and Reasoning
Authors: Sridhar Dasaratha, Sai Akhil Puranam, Karmvir Singh Phogat, Sunil Reddy Tiyyagura, Nigel P. Duffy
IJCAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Evaluation on three different tasks demonstrates that Deep PSL significantly outperforms state-of-the-art neuro-symbolic methods on scalability while achieving comparable or better accuracy. |
| Researcher Affiliation | Industry | Sridhar Dasaratha1 , Sai Akhil Puranam1 , Karmvir Singh Phogat1 , Sunil Reddy Tiyyagura1 , Nigel P. Duffy2 1 EY Global Delivery Services India LLP 2 Ernst & Young (EY) LLP USA |
| Pseudocode | Yes | Algorithm 1 Joint optimization: backpropagating loss to the neural network |
| Open Source Code | No | The paper does not include an explicit statement about releasing the source code for Deep PSL or provide a direct link to a code repository for their methodology. |
| Open Datasets | Yes | The goal of this task is to predict the sum of digits present in two MNIST images [Manhaeve et al., 2018]. ... We use data from the Cora and Citeseer scientific datasets [Yang et al., 2016]. |
| Dataset Splits | Yes | Each of these tasks contains train, validation and test splits in the corresponding dataset(s). ... Table 4: Dataset splits for semi-supervised classification task (e.g., Cora: 140/ 500/ 1000 Train/ Val/ Test). |
| Hardware Specification | Yes | The experiments are performed on a Mac Book Pro with 2.6GHz Intel i7 processor having 6 cores. |
| Software Dependencies | No | The paper mentions software like TensorFlow in the context of related work but does not provide specific version numbers for any software dependencies used in their own experimental setup. |
| Experiment Setup | Yes | Table 1: Hyperparameters used for Deep PSL [lists Optimizer, Learning rate, Max iterations, ฮฑ, ยต, Update steps, Epochs]. ... The CNN consists of two convolution (CONV) layers with 32 and 64 filters... This is followed by two fully connected layers with 128 and 10 nodes... A batch size of 16 is used for training. |