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Training Complex Models with Multi-Task Weak Supervision., , , , , and . AAAI, page 4763-4771. AAAI Press, (2019)AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels., , , , , , , , , and . NeurIPS, (2022)Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation., , , , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 3286-3294. PMLR, (2021)Low-Dimensional Hyperbolic Knowledge Graph Embeddings., , , , , and . ACL, page 6901-6914. Association for Computational Linguistics, (2020)The Cost of Compression: Investigating the Impact of Compression on Parametric Knowledge in Language Models., , , and . EMNLP (Findings), page 5255-5273. Association for Computational Linguistics, (2023)OTTER: Improving Zero-Shot Classification via Optimal Transport., , , , and . CoRR, (2024)Shoring up the foundations: fusing model embeddings and weak supervision., , , , , , and . UAI, volume 180 of Proceedings of Machine Learning Research, page 357-367. PMLR, (2022)Pearls from Pebbles: Improved Confidence Functions for Auto-labeling., , , , , and . CoRR, (2024)Learning Dependency Structures for Weak Supervision Models., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 6418-6427. PMLR, (2019)Lifting Weak Supervision To Structured Prediction., and . NeurIPS, (2022)