DIP: Efficient Large Multimodal Model Training with Dynamic Interleaved Pipeline
The three stages of DIP’s pipeline schedule searchAbstract
Review of paper writing approach, summarizing research themes and innovations, sharing paper submission experiences.
Date
Jun 10, 2026 8:30 AM — 9:15 AM
Event
DIP: Efficient Large Multimodal Model Training with Dynamic Interleaved Pipeline
Location
Room 101, Xinda Building B
Authors
Hao Yao
(he/him)
M.S. Student
Master’s student at CUIT. Research focuses on optimization of model and data heterogeneity in large-scale training of Multimodal Large Language Models (MLLM).