12 citations · 14 across the 4 of their papers we have counts for
4 papers
Tri-Info: Generalizable, Interpretable Failure Prediction for VLA Models via Information Theory
Jinghan Yang, Yunchao Zhang, Wang Yuan +4
Vision-Language-Action (VLA) models are increasingly deployed across diverse tasks, yet they remain black boxes whose physical interactions can cause irreversible harm, making gene…
When to Pre-Train Graph Neural Networks? From Data Generation Perspective!
Yuxuan Cao, Jiarong Xu, Carl Yang +5
In recent years, graph pre-training has gained significant attention, focusing on acquiring transferable knowledge from unlabeled graph data to improve downstream performance. Desp…
Navigation as Attackers Wish? Towards Building Robust Embodied Agents under Federated Learning
Yunchao Zhang, Zonglin Di, Kaiwen Zhou +2
Federated embodied agent learning protects the data privacy of individual visual environments by keeping data locally at each client (the individual environment) during training. H…
Universal Prompt Tuning for Graph Neural Networks
Taoran Fang, Yunchao Zhang, Yang Yang +2
In recent years, prompt tuning has sparked a research surge in adapting pre-trained models. Unlike the unified pre-training strategy employed in the language field, the graph field…