Have LLMs Made Active Learning Obsolete? Surveying the NLP Community
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Julius Gonsior
jgonsior
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Active Learning
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Have LLMs Made Active Learning Obsolete? Surveying the NLP Community
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๐ก๐๐ผ๐ผ๐ธ๐ถ๐ป๐ด ๐ณ๐ผ๐ฟ ๐๐๐ฝ๐ฝ๐ผ๐ฟ๐: ๐๐ฎ๐๐ฒ ๐๐ผ๐ ๐ฒ๐๐ฒ๐ฟ ๐ต๐ฎ๐ฑ ๐๐ผ ๐ผ๐๐ฒ๐ฟ๐ฐ๐ผ๐บ๐ฒ ๐ฎ ๐น๐ฎ๐ฐ๐ธ ๐ผ๐ณ ๐น๐ฎ๐ฏ๐ฒ๐น๐ฒ๐ฑ ๐ฑ๐ฎ๐๐ฎ ๐๐ผ ๐ฑ๐ฒ๐ฎ๐น ๐๐ถ๐๐ต ๐ฎ๐ป ๐ก๐๐ฃ ๐๐ฎ๐๐ธ?
Are you working on Natural Language Processing tasks and have faced the challenge of a lack of labeled data before? ๐ช๐ฒ ๐ฎ๐ฟ๐ฒ ๐ฐ๐๐ฟ๐ฟ๐ฒ๐ป๐๐น๐ ๐ฐ๐ผ๐ป๐ฑ๐๐ฐ๐๐ถ๐ป๐ด ๐ฎ ๐๐๐ฟ๐๐ฒ๐ to explore the strategies used to address this bottleneck, especially in the context of recent advancements, including but not limited to large language models.
The survey is non-commercial and conducted solely for academic research purposes. The results will contribute to an open-access publication that also benefits the community.
๐ With only 5โ15 minutes of your time, you would greatly help to investigate which strategies are used by the #NLP community to overcome a lack of labeled data.
โค๏ธHow you can help even more: If you know others working on supervised learning and NLP, please share this survey with themโweโd really appreciate it!
Survey: https://bildungsportal.sachsen.de/umfragen/limesurvey/index.php/538271
Estimated time required: 5โ15 minutes
Deadline for participation: January 12, 2025
#NLP #ML
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ImitAL: Learning Active Learning Strategies from Synthetic Data
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