5 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 5 cited
Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
Jun Yu, Yutong Dai, Xiaokang Liu +14
MTL is a learning paradigm that effectively leverages both task-specific and shared information to address multiple related tasks simultaneously. In contrast to STL, MTL offers a s…
cs.CV2023★ 3 cited
Robust Computer Vision in an Ever-Changing World: A Survey of Techniques for Tackling Distribution Shifts
Eashan Adhikarla, Kai Zhang, Jun Yu +3
AI applications are becoming increasingly visible to the general public. There is a notable gap between the theoretical assumptions researchers make about computer vision models an…