83 citations · 94 across the 7 of their papers we have counts for
7 papers
Guided Cooperation in Hierarchical Reinforcement Learning via Model-based Rollout
Haoran Wang, Zeshen Tang, Leya Yang +4
Goal-conditioned hierarchical reinforcement learning (HRL) presents a promising approach for enabling effective exploration in complex, long-horizon reinforcement learning (RL) tas…
Artificial-Spiking Hierarchical Networks for Vision-Language Representation Learning
Yeming Chen, Siyu Zhang, Yaoru Sun +2
With the success of self-supervised learning, multimodal foundation models have rapidly adapted a wide range of downstream tasks driven by vision and language (VL) pretraining. Sta…
LOIS: Looking Out of Instance Semantics for Visual Question Answering
Siyu Zhang, Yeming Chen, Yaoru Sun +3
Visual question answering (VQA) has been intensively studied as a multimodal task that requires effort in bridging vision and language to infer answers correctly. Recent attempts h…
Task-oriented Memory-efficient Pruning-Adapter
Guorun Wang, Jun Yang, Yaoru Sun
The Outstanding performance and growing size of Large Language Models has led to increased attention in parameter efficient learning. The two predominant approaches are Adapters an…
Pixel Difference Convolutional Network for RGB-D Semantic Segmentation
Jun Yang, Lizhi Bai, Yaoru Sun +3
RGB-D semantic segmentation can be advanced with convolutional neural networks due to the availability of Depth data. Although objects cannot be easily discriminated by just the 2D…
DCANet: Differential Convolution Attention Network for RGB-D Semantic Segmentation
Lizhi Bai, Jun Yang, Chunqi Tian +4
Combining RGB images and the corresponding depth maps in semantic segmentation proves the effectiveness in the past few years. Existing RGB-D modal fusion methods either lack the n…