2 citations · 3 across the 12 of their papers we have counts for
7 papers · 1 filter
How Should World Models Be Evaluated for Embodied Decision-Making? A Decision-Making-Centric Position
Yang Yu, Shiyuan Zhang, Yifei Sheng +2
World models have become a central abstraction in modern AI. The term now refers to several different objects: action-conditioned environment models, latent imagination models, fut…
Self-Distilled Policy Gradient
Yifeng Liu, Shiyuan Zhang, Yifan Zhang +1
On-policy self-distillation, where a language model conditions on privileged context to supervise its own generations, is a promising source of dense supervision for sparse-reward…
U-MASK: User-adaptive Spatio-Temporal Masking for Personalized Mobile AI Applications
Shiyuan Zhang, Yilai Liu, Yuwei Du +3
Personalized mobile artificial intelligence applications are widely deployed, yet they are expected to infer user behavior from sparse and irregular histories under a continuously…
Exploring Training Data Attribution under Limited Access Constraints
Shiyuan Zhang, Junwei Deng, Juhan Bae +1
Training data attribution (TDA) plays a critical role in understanding the influence of individual training data points on model predictions. Gradient-based TDA methods, popularize…
Taming Hyperparameter Sensitivity in Data Attribution: Practical Selection Without Costly Retraining
Weiyi Wang, Junwei Deng, Yuzheng Hu +5
Data attribution methods, which quantify the influence of individual training data points on a machine learning model, have gained increasing popularity in data-centric application…
Energy-Weighted Flow Matching for Offline Reinforcement Learning
Shiyuan Zhang, Weitong Zhang, Quanquan Gu
This paper investigates energy guidance in generative modeling, where the target distribution is defined as , with $…
: A Library for Efficient Data Attribution
Junwei Deng, Ting-Wei Li, Shiyuan Zhang +7
Data attribution methods aim to quantify the influence of individual training samples on the prediction of artificial intelligence (AI) models. As training data plays an increasing…