3 citations · 6 across the 6 of their papers we have counts for
6 papers
HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM
Zhilin Wang, Yi Dong, Jiaqi Zeng +8
Existing open-source helpfulness preference datasets do not specify what makes some responses more helpful and others less so. Models trained on these datasets can incidentally lea…
Humanoid Agents: Platform for Simulating Human-like Generative Agents
Zhilin Wang, Yu Ying Chiu, Yu Cheung Chiu
Just as computational simulations of atoms, molecules and cells have shaped the way we study the sciences, true-to-life simulations of human-like agents can be valuable tools for s…
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Yi Dong, Zhilin Wang, Makesh Narsimhan Sreedhar +2
Model alignment with human preferences is an essential step in making Large Language Models (LLMs) helpful and consistent with human values. It typically consists of supervised fin…
PoFEL: Energy-efficient Consensus for Blockchain-based Hierarchical Federated Learning
Shengyang Li, Qin Hu, Zhilin Wang
Facilitated by mobile edge computing, client-edge-cloud hierarchical federated learning (HFL) enables communication-efficient model training in a widespread area but also incurs ad…
Straggler Mitigation and Latency Optimization in Blockchain-based Hierarchical Federated Learning
Zhilin Wang, Qin Hu, Minghui Xu +1
Cloud-edge-device hierarchical federated learning (HFL) has been recently proposed to achieve communication-efficient and privacy-preserving distributed learning. However, there ex…
Blockchain-based Edge Resource Sharing for Metaverse
Zhilin Wang, Qin Hu, Minghui Xu +1
Although Metaverse has recently been widely studied, its practical application still faces many challenges. One of the severe challenges is the lack of sufficient resources for com…