7 citations · 21 across the 10 of their papers we have counts for
10 papers
Uncertainty-Penalized Reinforcement Learning from Human Feedback with Diverse Reward LoRA Ensembles
Yuanzhao Zhai, Han Zhang, Yu Lei +5
Reinforcement learning from human feedback (RLHF) emerges as a promising paradigm for aligning large language models (LLMs). However, a notable challenge in RLHF is overoptimizatio…
Diversifying Message Aggregation in Multi-Agent Communication via Normalized Tensor Nuclear Norm Regularization
Yuanzhao Zhai, Kele Xu, Bo Ding +3
Aggregating messages is a key component for the communication of multi-agent reinforcement learning (Comm-MARL). Recently, it has witnessed the prevalence of graph attention networ…
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning
Zijian Gao, Kele Xu, Yuanzhao Zhai +4
Under sparse extrinsic reward settings, reinforcement learning has remained challenging, despite surging interests in this field. Previous attempts suggest that intrinsic reward ca…
Dynamic Memory-based Curiosity: A Bootstrap Approach for Exploration
Zijian Gao, YiYing Li, Kele Xu +5
The sparsity of extrinsic rewards poses a serious challenge for reinforcement learning (RL). Currently, many efforts have been made on curiosity which can provide a representative…
Nuclear Norm Maximization Based Curiosity-Driven Learning
Chao Chen, Zijian Gao, Kele Xu +5
To handle the sparsity of the extrinsic rewards in reinforcement learning, researchers have proposed intrinsic reward which enables the agent to learn the skills that might come in…
FINT: Field-aware INTeraction Neural Network For CTR Prediction
Zhishan Zhao, Sen Yang, Guohui Liu +2
As a critical component for online advertising and marking, click-through rate (CTR) prediction has draw lots of attentions from both industry and academia field. Recently, the dee…