24 citations · 37 across the 5 of their papers we have counts for
5 papers
Multimodal Graph Transformer for Multimodal Question Answering
Xuehai He, Xin Eric Wang
Despite the success of Transformer models in vision and language tasks, they often learn knowledge from enormous data implicitly and cannot utilize structured input data directly.…
A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges
Xuansheng Wu, Kaixiong Zhou, Mingchen Sun +2
The recent "pre-train, prompt, predict training" paradigm has gained popularity as a way to learn generalizable models with limited labeled data. The approach involves using a pre-…
PanGu-Coder: Program Synthesis with Function-Level Language Modeling
Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta +19
We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i.e. the synthesis of programming language solut…
Understanding Instance-Level Impact of Fairness Constraints
Jialu Wang, Xin Eric Wang, Yang Liu
A variety of fairness constraints have been proposed in the literature to mitigate group-level statistical bias. Their impacts have been largely evaluated for different groups of p…
OOD-GNN: Out-of-Distribution Generalized Graph Neural Network
Haoyang Li, Xin Wang, Ziwei Zhang +1
Graph neural networks (GNNs) have achieved impressive performance when testing and training graph data come from identical distribution. However, existing GNNs lack out-of-distribu…