ConStruct-VL: Data-Free Continual Structured VL Concepts Learning*

Author:

Smith James Seale1,Cascante-Bonilla Paola1,Arbelle Assaf2,Kim Donghyun1,Panda Rameswar1,Cox David1,Yang Diyi3,Kira Zsolt4,Feris Rogerio1,Karlinsky Leonid1

Affiliation:

1. MIT-IBM Watson AI Lab

2. IBM Research

3. Stanford University

4. Georgia Institute of Technology

Funder

Defense Advanced Research Projects Agency

Publisher

IEEE

Reference68 articles.

1. Parameter-efficient transfer learning for nlp;houlsby;International Conference on Machine Learning,0

2. A simple baseline for zero-shot semantic segmentation with pre-trained vision-language model;xu;ArXiv Preprint,2021

3. Learning a unified classifier incrementally via re-balancing;hou;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,0

4. Learning to Prompt for Continual Learning

5. Lora: Low-rank adaptation of large language models;hu;ArXiv Preprint,2021

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