23 citations · 25 across the 6 of their papers we have counts for
6 papers
Reward-Driven Interaction: Enhancing Proactive Dialogue Agents through User Satisfaction Prediction
Wei Shen, Xiaonan He, Chuheng Zhang +3
Reward-driven proactive dialogue agents require precise estimation of user satisfaction as an intrinsic reward signal to determine optimal interaction strategies. Specifically, thi…
Policy Filtration for RLHF to Mitigate Noise in Reward Models
Chuheng Zhang, Wei Shen, Li Zhao +4
While direct policy optimization methods exist, pioneering LLMs are fine-tuned with reinforcement learning from human feedback (RLHF) to generate better responses under the supervi…
RePreM: Representation Pre-training with Masked Model for Reinforcement Learning
Yuanying Cai, Chuheng Zhang, Wei Shen +3
Inspired by the recent success of sequence modeling in RL and the use of masked language model for pre-training, we propose a masked model for pre-training in RL, RePreM (Represent…
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
Yuanying Cai, Chuheng Zhang, Li Zhao +6
We consider an offline reinforcement learning (RL) setting where the agent need to learn from a dataset collected by rolling out multiple behavior policies. There are two challenge…
Inductive Matrix Completion Using Graph Autoencoder
Wei Shen, Chuheng Zhang, Yun Tian +4
Recently, the graph neural network (GNN) has shown great power in matrix completion by formulating a rating matrix as a bipartite graph and then predicting the link between the cor…
Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing
Wei Shen, Xiaonan He, Chuheng Zhang +3
In mobile crowdsourcing (MCS), the platform selects participants to complete location-aware tasks from the recruiters aiming to achieve multiple goals (e.g., profit maximization, e…