15 citations · 50 across the 14 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2025
MEPT: Mixture of Expert Prompt Tuning as a Manifold Mapper
Runjia Zeng, Guangyan Sun, Qifan Wang +8
Considering deep neural networks as manifold mappers, the pretrain-then-fine-tune paradigm can be interpreted as a two-stage process: pretrain establishes a broad knowledge base, a…
cs.LG2025★ 2 cited
Re-Imagining Multimodal Instruction Tuning: A Representation View
Yiyang Liu, James Chenhao Liang, Ruixiang Tang +8
Multimodal instruction tuning has proven to be an effective strategy for achieving zero-shot generalization by fine-tuning pre-trained Large Multimodal Models (LMMs) with instructi…