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cs.CL2025
In-Context Learning on a Budget: A Case Study in Token Classification
Uri Berger, Tal Baumel, Gabriel Stanovsky
Few shot in-context learning (ICL) typically assumes access to large annotated training sets. However, in many real world scenarios, such as domain adaptation, there is only a limi…
cs.CL2024
Controllable Synthetic Clinical Note Generation with Privacy Guarantees
Tal Baumel, Andre Manoel, Daniel Jones +5
In the field of machine learning, domain-specific annotated data is an invaluable resource for training effective models. However, in the medical domain, this data often includes P…