NeurIPS 2024 Workshop on Adaptive Foundation Models

Call for Papers


Important Dates and Links

Submission Site https://openreview.net/group?id=NeurIPS.cc/2024/Workshop/AFM
Submission Site Opens September 2, 2024
Submission Deadline October 4, 2024, 23:59 AoE
Countdown:
Decisions Announced October 9, 2024, AoE
Countdown:
Camera-Ready Due TBD
Workshop Location and Date Exhibit Hall A, December 14, 2024

Call for Papers

We are sourcing short, four-page papers focusing on discrete abstractions such as objects, concepts, and events and the causal structure that relates them. Specific topics of interest include:

Continual Weight Updates

Techniques and challenges in updating model weights continually to adapt to new information without forgetting previously learned knowledge.

Efficient Fine-Tuning

Strategies to fine-tune models in a resource-efficient manner, enabling broader application without compromising performance.

Token/Prompt Tuning

Exploration of lightweight methods to adapt large models to specific tasks or domains through token or prompt modifications.

In-Context Learning/Few-Shot Learning

Mechanisms for models to learn from context within a limited interaction, and learn new concepts or tasks with very few examples.

Personalized Adaptation

Techniques for customizing models to individual user preferences, tasks, or domains, ensuring more relevant and effective interactions.

Retrieval-Augmented Generation

Integration of external knowledge sources to enhance the generation capabilities of models, facilitating more informed and contextually relevant outputs.

Multimodal Learning

Techniques for leveraging data from multiple modalities (e.g., text, images, robot interactions) into a unified framework, yielding rich interactivity.

Submission Policy

  • We encourage 4 page submissions but are enforcing a hard maximum of 5, plus any number of pages for references and supplementary material. We ask authors to use the supplementary material only for minor details that do not fit in the main paper. We reserve the right to desk reject papers that strongly violate this format (e.g. more than 5 pages main content before references)
  • Submissions should be fully anonymized for double-blind review.
  • Papers should use the NeurIPS style file.
  • Accepted submissions will appear on the workshop website (non-archival).

If you have any questions, please reach out to: neurips2024-adaptive-foundation@googlegroups.com