Scalable Continual Learning for Lifelong Foundation Models workshop (@NeurIPS 2024)
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Beyza Ermiş
Aug 30, 2024, 7:41:33 AM8/30/24
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Hi all,
We are glad to announce Scalable Continual Learning for Lifelong Foundation Models workshop at NeurIPS 2024 and are now accepting submissions!
At this workshop, we discuss recent advances in scalable CL that could replace static foundation model (FM) training, enabling us to model dynamic real-world information. We bring experts and researchers from various domains, including language, vision, speech, and multimodal ML to exchange ideas and foster collaboration.
Call for Papers:
We welcome all contributions related to scaling the continual learning of foundation models. Potential areas of interest include but are not limited to:
- How should CL methods be utilized to avoid retraining large, foundation models?
- How can we address the challenge of catastrophic forgetting when fine-tuning FMs on considerably smaller and less diverse datasets compared to the extensive pretraining datasets?
- How can we address CL on a large scale when dealing with real-world problems with domain shifts and long-tailed data distributions?
- How can insights from other fields (online learning, meta-learning, reinforcement learning, neuroscience, AutoML, etc) inform and advance our CL of FMs?
- Does combining FMs with structured knowledge sources (databases, knowledge graphs, etc) help CL?
- What are the key considerations in designing benchmarks, evaluation protocols, and appropriate metrics for assessing CL of FMs?
- How can recent advances in FMs enhance CL techniques?
- What strategies can facilitate the seamless integration of CL and multi-modal learning systems?
Important dates:
Submission deadline: September 09, 23:59 AoE.
Decision notification: October 09, 2024, AoE.
Website: https://sites.google.com/view/continual-fomo-workshop/
For any questions, email us at: continu...@googlegroups.com
We look forward to your participation and contributions!
Best,
Scalable Continual Learning Workshop Organizing Team
We are glad to announce Scalable Continual Learning for Lifelong Foundation Models workshop at NeurIPS 2024 and are now accepting submissions!
At this workshop, we discuss recent advances in scalable CL that could replace static foundation model (FM) training, enabling us to model dynamic real-world information. We bring experts and researchers from various domains, including language, vision, speech, and multimodal ML to exchange ideas and foster collaboration.
Call for Papers:
We welcome all contributions related to scaling the continual learning of foundation models. Potential areas of interest include but are not limited to:
- How should CL methods be utilized to avoid retraining large, foundation models?
- How can we address the challenge of catastrophic forgetting when fine-tuning FMs on considerably smaller and less diverse datasets compared to the extensive pretraining datasets?
- How can we address CL on a large scale when dealing with real-world problems with domain shifts and long-tailed data distributions?
- How can insights from other fields (online learning, meta-learning, reinforcement learning, neuroscience, AutoML, etc) inform and advance our CL of FMs?
- Does combining FMs with structured knowledge sources (databases, knowledge graphs, etc) help CL?
- What are the key considerations in designing benchmarks, evaluation protocols, and appropriate metrics for assessing CL of FMs?
- How can recent advances in FMs enhance CL techniques?
- What strategies can facilitate the seamless integration of CL and multi-modal learning systems?
Important dates:
Submission deadline: September 09, 23:59 AoE.
Decision notification: October 09, 2024, AoE.
Website: https://sites.google.com/view/continual-fomo-workshop/
For any questions, email us at: continu...@googlegroups.com
We look forward to your participation and contributions!
Best,
Scalable Continual Learning Workshop Organizing Team
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