cl4fm.github.io
Contrastive Learning for Foundation Models and Beyond
This site is the official site for KDD 2024 tutorial on Heterogeneous Contrastive Learning for Foundation Models and Beyond.
- Time: 10:00 AM – 1:00 PM, Sunday, August 25th, 2024
- Place: Barcelona, Spain
Audience and Topic
The tutorial is designed for anyone with basic knowledge of machine learning and artificial intelligence. This tutorial will provide the audience with the basic concept of heterogeneous contrastive learning and how contrastive learning is applied to train and fine-tune the foundation models for view and task heterogeneity. After attending this tutorial, the audience will be familiar with the mechanism of contrastive learning in many domains, such as text mining, image recognition, etc.
Agenda
Opening Remark [slides]
- Overview of contrastive learning (20min)
- Contrastive Learning with View Heterogeneity (65min)
- Contrastive Learning Basis
- Contrastive Foundation Models (Vision Models, Language Models, Multi-modal Models, etc.)
Coffee Break (15min)
- Contrastive Learning with Task Heterogeneity (60min)
- Pre-training tasks (Pretext Tasks, Supervised Tasks, Preference Tasks, etc. )
- Downstream tasks (Typical Downstream Tasks, Auto ML, Prompting Learning, Multi-task Learning, etc)
- Open Challenges and Future Directions (10min)
- Q&A (10min)
Material
Reference
@article{DBLP:journals/corr/abs-2404-00225,
author = {Lecheng Zheng and
Baoyu Jing and
Zihao Li and
Hanghang Tong and
Jingrui He},
title = {Heterogeneous Contrastive Learning for Foundation Models and Beyond},
journal = {CoRR},
volume = {abs/2404.00225},
year = {2024},
url = {https://doi.org/10.48550/arXiv.2404.00225},
doi = {10.48550/ARXIV.2404.00225},
eprinttype = {arXiv},
eprint = {2404.00225},
timestamp = {Wed, 08 May 2024 17:22:41 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2404-00225.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}