2 citations · 2 across the 7 of their papers we have counts for
7 papers
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao +4
Interactive 3D segmentation has emerged as a promising solution for generating accurate object masks in complex 3D scenes by incorporating user-provided clicks. However, two critic…
Proactive Gradient Conflict Mitigation in Multi-Task Learning: A Sparse Training Perspective
Zhi Zhang, Jiayi Shen, Congfeng Cao +5
Advancing towards generalist agents necessitates the concurrent processing of multiple tasks using a unified model, thereby underscoring the growing significance of simultaneous mo…
SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents
Dawei Li, Zhen Tan, Peijia Qian +4
While multi-agent systems have been shown to significantly enhance the performance of Large Language Models (LLMs) across various tasks and applications, the dense interaction betw…
Any-Shift Prompting for Generalization over Distributions
Zehao Xiao, Jiayi Shen, Mohammad Mahdi Derakhshani +2
Image-language models with prompt learning have shown remarkable advances in numerous downstream vision tasks. Nevertheless, conventional prompt learning methods overfit their trai…
Episodic Multi-Task Learning with Heterogeneous Neural Processes
Jiayi Shen, Xiantong Zhen, Qi +2
This paper focuses on the data-insufficiency problem in multi-task learning within an episodic training setup. Specifically, we explore the potential of heterogeneous information a…
Prototype-Enhanced Hypergraph Learning for Heterogeneous Information Networks
Shuai Wang, Jiayi Shen, Athanasios Efthymiou +4
The variety and complexity of relations in multimedia data lead to Heterogeneous Information Networks (HINs). Capturing the semantics from such networks requires approaches capable…