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cs.LG2025
Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
Tianjun Yao, Haoxuan Li, Yongqiang Chen +4
Graph Neural Networks (GNNs) often encounter significant performance degradation under distribution shifts between training and test data, hindering their applicability in real-wor…
cs.LG2025
Concept Concentration for Faithful Representation Intervention
Hongzheng Yang, Yongqiang Chen, Zeyu Qin +4
Representation intervention aims to localize and modify the representations that encode the underlying concepts in large language models (LLMs) to elicit the aligned and expected b…
cs.AI2025★ 1 cited
Can Large Language Models Help Experimental Design for Causal Discovery?
Junyi Li, Yongqiang Chen, Chenxi Liu +5
Designing proper experiments and selecting optimal intervention targets is a longstanding problem in scientific or causal discovery. Identifying the underlying causal structure fro…