Request Correction
Use this form to request corrections to the paper metadata. Select the fields that need correction and provide the correct information.
Correction Guidelines
- Click the edit button next to a field to report a correction.
- Fill in the suggested correction value for each field you want to correct.
- Provide your name and email so we can contact you if needed.
Paper Information
CrisisCL: A Domain Incremental Learning Benchmark for Crisis Management
Paper Fields
Click the edit button next to a field to report a correction.
CrisisCL: A Domain Incremental Learning Benchmark for Crisis Management
This paper proposes CrisisCL, a domain incremental learning benchmark for crisis management. Based on previous crisis management protocols, it improves consistency by allowing continual learning (CL) of new crises. A set of experiments have been conducted on multilingual datasets relying on continual learning methods and transformers to improve performance and ensure model generalization. Results reveal that regularization methods are more effective on large, coherent domains, whereas replay strategies struggle under constrained memory. Additional experimental protocols further expose the limitations of current CL methods when generalizing to unforeseen crisis events.
Authors
Expand an author to correct their information. Use the remove button to request author removal, or add a new author.
PDF Attachment
You may attach a PDF as a corrected version of the paper. Max file size: 10MB. Only PDF files are accepted.
Your Information
Author Declaration *
Select at least one field to correct using the edit buttons above.