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cs.LG2026
Quantifying Explanation Quality in Graph Neural Networks using Out-of-Distribution Generalization
Ding Zhang, Siddharth Betala, Chirag Agarwal
Evaluating the quality of post-hoc explanations for Graph Neural Networks (GNNs) remains a significant challenge. While recent years have seen an increasing development of explaina…
cs.LG2026
A Mechanistic Perspective and Circuit-Guided Difficulty Metric for Unlearning
Jiali Cheng, Ziheng Chen, Chirag Agarwal +1
Machine unlearning is becoming essential for building trustworthy and compliant language models. Yet unlearning success varies considerably across individual samples: some are reli…
cs.LG2025
Do Students Debias Like Teachers? On the Distillability of Bias Mitigation Methods
Jiali Cheng, Chirag Agarwal, Hadi Amiri
Knowledge distillation (KD) is an effective method for model compression and transferring knowledge between models. However, its effect on model's robustness against spurious corre…