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cs.CL2024
Continuous Language Model Interpolation for Dynamic and Controllable Text Generation
Sara Kangaslahti, David Alvarez-Melis
As large language models (LLMs) have gained popularity for a variety of use cases, making them adaptable and controllable has become increasingly important, especially for user-fac…
cs.CL2022
Can You Label Less by Using Out-of-Domain Data? Active & Transfer Learning with Few-shot Instructions
Rafal Kocielnik, Sara Kangaslahti, Shrimai Prabhumoye +3
Labeling social-media data for custom dimensions of toxicity and social bias is challenging and labor-intensive. Existing transfer and active learning approaches meant to reduce an…