Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision

Liger, a combination of foundation models and weak supervision frameworks, improves existing weak supervision techniques by partitioning the embedding space and extending source votes in embedding space, resulting in improved performance on six benchmark NLP and video tasks.