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cs.LG2026
Towards Long-Horizon Interpretability: Efficient and Faithful Multi-Token Attribution for Reasoning LLMs
Wenbo Pan, Zhichao Liu, Xianlong Wang +2
Token attribution methods provide intuitive explanations for language model outputs by identifying causally important input tokens. However, as modern LLMs increasingly rely on ext…
cs.LG2025
Exploring Incremental Unlearning: Techniques, Challenges, and Future Directions
Sadia Qureshi, Thanveer Shaik, Xiaohui Tao +4
The growing demand for data privacy in Machine Learning (ML) applications has seen Machine Unlearning (MU) emerge as a critical area of research. As the `right to be forgotten' bec…