-
AdaMerging: Adaptive Model Merging for Multi-Task Learning
Paper • 2310.02575 • Published • 1 -
Localizing Task Information for Improved Model Merging and Compression
Paper • 2405.07813 • Published -
Tint Your Models Task-wise for Improved Multi-task Model Merging
Paper • 2412.19098 • Published • 3 -
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Paper • 2501.01230 • Published
Zedong Wang
JackyWangAI
AI & ML interests
Computer Vision, Multi-task Learning.
Recent Activity
upvoted
a
paper
29 days ago
3D-R1: Enhancing Reasoning in 3D VLMs for Unified Scene Understanding
upvoted
a
paper
about 1 month ago
Mix Data or Merge Models? Optimizing for Diverse Multi-Task Learning
updated
a collection
about 1 month ago
Model Merging
Organizations
-
STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data Map
Paper • 2307.03374 • Published • 1 -
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
Paper • 2304.04959 • Published • 2 -
Improvable Gap Balancing for Multi-Task Learning
Paper • 2307.15429 • Published • 1 -
Understanding and Improving Information Transfer in Multi-Task Learning
Paper • 2005.00944 • Published • 1
-
AdaMerging: Adaptive Model Merging for Multi-Task Learning
Paper • 2310.02575 • Published • 1 -
Localizing Task Information for Improved Model Merging and Compression
Paper • 2405.07813 • Published -
Tint Your Models Task-wise for Improved Multi-task Model Merging
Paper • 2412.19098 • Published • 3 -
Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent
Paper • 2501.01230 • Published
-
STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data Map
Paper • 2307.03374 • Published • 1 -
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
Paper • 2304.04959 • Published • 2 -
Improvable Gap Balancing for Multi-Task Learning
Paper • 2307.15429 • Published • 1 -
Understanding and Improving Information Transfer in Multi-Task Learning
Paper • 2005.00944 • Published • 1
models
0
None public yet
datasets
0
None public yet