Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning
Authors: Hongzhan Lin, Pengyao Yi, Jing Ma, Haiyun Jiang, Ziyang Luo, Shuming Shi, Ruifang Liu
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments conducted on three real-world datasets demonstrate that our proposed model achieves much better performance than state-of-the-art methods and exhibits a superior capacity for detecting rumors at early stages. |
| Researcher Affiliation | Academia | Hong Kong Baptist University 2Beijing University of Posts and Telecommunications 3Fudan University 4Tsinghua University |
| Pseudocode | No | The paper describes the approach in detail but does not provide any pseudocode or algorithm blocks. |
| Open Source Code | Yes | Our code and resources will be available at https://github.com/ Pengyao Yi/zero Rumor AAAI |
| Open Datasets | Yes | We utilize FOUR public datasets TWITTER, WEIBO (Ma et al. 2016), Twitter-COVID19 and Weibo-COVID19 (Lin et al. 2022) for experiments. |
| Dataset Splits | No | The paper mentions 'Early stopping (Yao, Rosasco, and Caponnetto 2007) is applied to avoid overfitting', which implies the use of a validation set. However, it does not provide specific details on the split percentages, sample counts, or methodology for the validation set. |
| Hardware Specification | No | The paper does not specify the hardware used for running experiments (e.g., specific GPU or CPU models, memory, or cloud computing instances with detailed specifications). |
| Software Dependencies | No | The paper mentions the use of 'multilingual PLMs' and 'Adam W optimizer' but does not provide specific version numbers for these or other software dependencies (e.g., Python, PyTorch, TensorFlow versions). |
| Experiment Setup | Yes | We set the layer number k of the Syn Encoder as 6. The learning rate is initialized as 1e-5. Early stopping (Yao, Rosasco, and Caponnetto 2007) is applied to avoid overfitting. |