LearnShapley: Learning to Predict Rankings of Facts Contribution Based on Query Logs. - Dana Arad; Daniel Deutch; Nave Frost (CIKM, 2022)

Diffusion Lens: Interpreting Text Encoders in Text-to-Image Pipelines. - Michael Toker; Hadas Orgad; Mor Ventura; Dana Arad; Yonatan Belinkov (ACL (1), 2024)

Predicting Fact Contributions from Query Logs with Machine Learning. - Dana Arad; Daniel Deutch; Nave Frost (EDBT, 2024)

ReFACT: Updating Text-to-Image Models by Editing the Text Encoder. - Dana Arad; Hadas Orgad; Yonatan Belinkov (NAACL-HLT, 2024)

MIB: A Mechanistic Interpretability Benchmark. - Aaron Mueller; Atticus Geiger; Sarah Wiegreffe; Dana Arad; Iván Arcuschin; Adam Belfki; Yik Siu Chan; Jaden Fiotto-Kaufman; Tal Haklay; Michael Hanna 001; Jing Huang; Rohan Gupta; et al. (CoRR, 2025)

SAEs Are Good for Steering - If You Select the Right Features. - Dana Arad; Aaron Mueller; Yonatan Belinkov (CoRR, 2025)

Same Task, Different Circuits: Disentangling Modality-Specific Mechanisms in VLMs. - Yaniv Nikankin; Dana Arad; Yossi Gandelsman; Yonatan Belinkov (CoRR, 2025)

CRISP: Persistent Concept Unlearning via Sparse Autoencoders. - Tomer Ashuach; Dana Arad; Aaron Mueller; Martin Tutek; Yonatan Belinkov (CoRR, 2025)