most citedReward Guidance for Reinforcement Learning Tasks Based on Large Language Models: The LMGT Framework

11 citations · 28 across the 9 of their papers we have counts for

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cs.LG2024★ 2 cited

Adaptive Learning on User Segmentation: Universal to Specific Representation via Bipartite Neural Interaction

Xiaoyu Tan, Yongxin Deng, Chao Qu +4

Recently, models for user representation learning have been widely applied in click-through-rate (CTR) and conversion-rate (CVR) prediction. Usually, the model learns a universal u…

cs.LG2024★ 11 cited

Reward Guidance for Reinforcement Learning Tasks Based on Large Language Models: The LMGT Framework

Yongxin Deng, Xihe Qiu, Jue Chen +1

The inherent uncertainty in the environmental transition model of Reinforcement Learning (RL) necessitates a delicate balance between exploration and exploitation. This balance is…