3 papers
cs.LG2026
Test Time Training for Supervised Causal Learning
Zizhen Deng, Jiaru Zhang, Rui Ding +5
Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from significant out-of-distribution gene…
cs.CL2026
CAST: Achieving Stable LLM-based Text Analysis for Data Analytics
Jinxiang Xie, Zihao Li, Wei He +3
Text analysis of tabular data relies on two core operations: \emph{summarization} for corpus-level theme extraction and \emph{tagging} for row-level labeling. A critical limitation…
cs.LG2025
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning
Jiaru Zhang, Rui Ding, Qiang Fu +6
Causal discovery is a structured prediction task that aims to predict causal relations among variables based on their data samples. Supervised Causal Learning (SCL) is an emerging…