2 citations · 2 across the 2 of their papers we have counts for
4 papers
Calibrated Cache Model for Few-Shot Vision-Language Model Adaptation
Kun Ding, Qiang Yu, Haojian Zhang +2
Cache-based approaches stand out as both effective and efficient for adapting vision-language models (VLMs). Nonetheless, the existing cache model overlooks three crucial aspects.…
Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt Tuning
Kun Ding, Haojian Zhang, Qiang Yu +3
We propose a generalized method for boosting the generalization ability of pre-trained vision-language models (VLMs) while fine-tuning on downstream few-shot tasks. The idea is rea…
Compositional Kronecker Context Optimization for Vision-Language Models
Kun Ding, Xiaohui Li, Qiang Yu +3
Context Optimization (CoOp) has emerged as a simple yet effective technique for adapting CLIP-like vision-language models to downstream image recognition tasks. Nevertheless, learn…
DCRNN: A Deep Cross approach based on RNN for Partial Parameter Sharing in Multi-task Learning
Jie Zhou, Qian Yu
In recent years, DL has developed rapidly, and personalized services are exploring using DL algorithms to improve the performance of the recommendation system. For personalized ser…