HARGAN: Heterogeneous Argument Attention Network for Persuasiveness Prediction
Authors: Kuo-Yu Huang, Hen-Hsen Huang, Hsin-Hsi Chen13045-13054
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results show that our methodology achieves the state-of-the-art performance in persuasiveness prediction on the Change My View dataset. |
| Researcher Affiliation | Academia | 1 Department of Computer Science and Information Engineering, National Taiwan University, Taiwan 2 Department of Computer Science, National Chengchi University, Taiwan 3 MOST Joint Research Center for AI Technology and All Vista Healthcare, Taiwan kyhuang@nlg.csie.ntu.edu.tw, hhhuang@nccu.edu.tw, hhchen@ntu.edu.tw |
| Pseudocode | No | No pseudocode or clearly labeled algorithm block found. |
| Open Source Code | Yes | Our code is publicly available for the research community.2 2https://github.com/seasa2016/Heterogeneous Argument Attention Network |
| Open Datasets | Yes | Our study is conducted on the Change My View (CMV) dataset (Tan et al. 2016). |
| Dataset Splits | Yes | Train Dev Test # trees 969 241 311 # pairs 14922 3504 5013 Avg. turns 2.87 2.96 2.83 Table 1: Statistic of changemyview. We randomly split the training set into two parts, 80% of instances for training and 20% of instances for validation. |
| Hardware Specification | No | No specific hardware details (e.g., CPU/GPU models, memory) used for running experiments are mentioned. |
| Software Dependencies | No | The paper mentions BERT, ELMO, Bi-LSTM, and NLTK, but does not provide specific version numbers for these software dependencies. |
| Experiment Setup | Yes | To prevent error propagation from the previous stage, we loosen the constraint for the structure to be a graph. That is to say, each ADU could link to more than one parent ADU. We compute the child-parent score between the current ADU and each candidate using Equation (4), and choose the top-k candidates to link with. In our experiment, k is set to three. ... where the activation function is elu (Clevert, Unterthiner, and Hochreiter 2016) and M, which is the number of attention head, is chosen to be 4 in our experiment. ... where α is set to be 0.01 in our experiment. |