Causal Learning in Question Quality Improvement

By Yichuan Li, Ruocheng Guo, Weiying Wang, Huan Liu. 2019

7 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Jundong Li
2. Ruocheng Guo
3. Huan Liu
4. Raha Moraffah
5. Lu Cheng
6. Mansooreh Karami
7. Adrienne Jeanisha Raglin
8. P. Richard Hahn

Citations in the corpus

• Causal Interpretability for Machine Learning - Problems, Methods and Evaluation (2020, background): “[58] provide a comprehensive survey on benchmark datasets for different causal tasks.”
• A Survey of Learning Causality with Data (2018, background): “Potential problems include handling (1) anomalies [1, 37], (2) treatment entanglement [151], (3) complex treatments [95] (e.g., image and text as treatment), (4) temporal observations [102, 132].”