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cs.LG2024★ 1 cited
Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
Yunseon Choi, Sangmin Bae, Seonghyun Ban +6
With the advent of foundation models, prompt tuning has positioned itself as an important technique for directing model behaviors and eliciting desired responses. Prompt tuning reg…
cs.LG2023★ 1 cited
Mildly Constrained Evaluation Policy for Offline Reinforcement Learning
Linjie Xu, Zhengyao Jiang, Jinyu Wang +2
Offline reinforcement learning (RL) methodologies enforce constraints on the policy to adhere closely to the behavior policy, thereby stabilizing value learning and mitigating the…