Order-Planning Neural Text Generation From Structured Data
Authors: Lei Sha, Lili Mou, Tianyu Liu, Pascal Poupart, Sujian Li, Baobao Chang, Zhifang Sui
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conducted experiments on the WIKIBIO dataset and achieve higher performance than previous methods in terms of BLEU, ROUGE, and NIST scores; we also performed ablation tests to analyze each component of our model. |
| Researcher Affiliation | Academia | Key Laboratory of Computational Linguistics, Ministry of Education; School of EECS, Peking Univeristy David R. Cheriton School of Computer Science, University of Waterloo |
| Pseudocode | No | The paper contains architectural diagrams and mathematical equations but no structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Code is available at https://sites.google.com/site/orderplanningnlg/ |
| Open Datasets | Yes | We used the newly published WIKIBIO dataset (Lebret, Grangier, and Auli 2016),4 which contains 728,321 biographies from Wiki Project Biography5 (originally from English Wikipedia, September 2015). 4https://github.com/DavidGrangier/wikipedia-biography-dataset |
| Dataset Splits | Yes | We applied the standard data split: 80% for training and 10% for testing, except that model selection was performed on a validaton subset of 1000 samples (based on BLEU-4). |
| Hardware Specification | No | No specific hardware details (like CPU/GPU models, memory, or specific computing environments) used for running experiments were provided. |
| Software Dependencies | No | The paper mentions 'Adam' as the optimization algorithm but does not specify any software libraries or their version numbers. |
| Experiment Setup | Yes | In our experiments, both words and table fields embeddings were 400-dimensional and LSTM layers were 500-dimensional. We used Adam (Kingma and Ba 2015) as the optimization algorithm with a batch size of 32; other hyperparameters were set to default values. |