Dear list members,

We invite you to participate in our web survey exploring how recent advancements in NLP, such as LLMs, have changed the need for labeled data in Supervised Machine Learning.

Survey details:

• Topic: Web survey on Data Annotation and Active Learning 
• Target group: Researchers and practitioners alike in the fields of NLP, Supervised Machine Learning, and Active Learning in particular (not required).
• Duration: ~15 minutes
• Deadline for participation: January 12, 2025
• Survey link: https://bildungsportal.sachsen.de/umfragen/limesurvey/index.php/538271

Why should I invest my time in this survey?

• Make an impact: Participate in a community-effort and help to gain a better understanding of the current state and open issues on methods that are used to overcome a lack of labeled data.
• Gain insights: Receive a report with key findings to incorporate these insights into research and development of new methods and technologies.

Thank you for considering participating in our survey!

If you have any questions or require additional information, please don’t hesitate to contact us directly at activelearningsurvey2024@gmail.com.

If you know colleagues or peers who might be interested, we’d be grateful if you could forward this survey to them as well.

Best regards,

Julia Romberg (GESIS - Leibniz Institute for the Social Sciences, Germany)

Christopher Schröder (Institut für Angewandte Informatik e. V., Germany)

Julius Gonsior (TUD Dresden University of Technology)

------------------------------------------------------------------------

Leibniz Institute for the Social Sciences

Julia Romberg

Computational Social Science, Team Data Science Methods

+49(221)47694-742