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Shihan Wu

6 papers hereh-index 6151 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author3

Across the 5 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.RO3

identity via Semantic Scholar / OpenAlex

activity
20232025
collaborators
Showing cs.CVShow all

3 papers · 1 filter

cs.CV2025

A Closer Look at Conditional Prompt Tuning for Vision-Language Models

Ji Zhang, Shihan Wu, Lianli Gao +3

Despite the great promise of Prompt Tuning (PT) in adapting large Vision-Language Pretrained Models (VLPMs) to downstream tasks, they often struggle to overcome the Base-New Tradeo…

cs.CV2024

Skip Tuning: Pre-trained Vision-Language Models are Effective and Efficient Adapters Themselves

Shihan Wu, Ji Zhang, Pengpeng Zeng +3

Prompt tuning (PT) has long been recognized as an effective and efficient paradigm for transferring large pre-trained vision-language models (VLMs) to downstream tasks by learning…

cs.CV2023

DePT: Decoupled Prompt Tuning

Ji Zhang, Shihan Wu, Lianli Gao +2

This work breaks through the Base-New Tradeoff (BNT)dilemma in prompt tuning, i.e., the better the tuned model generalizes to the base (or target) task, the worse it generalizes to…

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