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cs.LG2026
Retrieval is Enough: Training-Free Interpretability with a Tool-Using Agent
Sriram Balasubramanian, Soheil Feizi
Interpretability methods for neural network activations span a wide cost spectrum, from cheap, training-free techniques (such as linear probes, PCA, SVD) to more expensive training…
cs.LG2025★ 1 cited
A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models
Zihao Lin, Samyadeep Basu, Mohammad Beigi +18
The rise of foundation models has transformed machine learning research, prompting efforts to uncover their inner workings and develop more efficient and reliable applications for…