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cs.LG2026
Stress Testing Unlearning Algorithms
Noam Diamant, Neta Glazer, Ethan Fetaya
Recently, machine unlearning, the removal of specific training data influence from a model, has gained increasing attention. In large language models (LLMs), unlearning is particul…
cs.LG2024
Multi Task Inverse Reinforcement Learning for Common Sense Reward
Neta Glazer, Aviv Navon, Aviv Shamsian +1
One of the challenges in applying reinforcement learning in a complex real-world environment lies in providing the agent with a sufficiently detailed reward function. Any misalignm…
cs.LG2023
Auxiliary Learning as an Asymmetric Bargaining Game
Aviv Shamsian, Aviv Navon, Neta Glazer +3
Auxiliary learning is an effective method for enhancing the generalization capabilities of trained models, particularly when dealing with small datasets. However, this approach may…