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07/26/2023
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models
The quality of training data impacts the performance of pre-trained larg...
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07/20/2023
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Recent work has shown that language models' (LMs) prompt-based learning ...
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12/20/2022
Resonant Anomaly Detection with Multiple Reference Datasets
An important class of techniques for resonant anomaly detection in high ...
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10/05/2022
Ask Me Anything: A simple strategy for prompting language models
Large language models (LLMs) transfer well to new tasks out-of-the-box s...
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04/18/2022
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval
Entity retrieval–retrieving information about entity mentions in a query...
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04/15/2022
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
An ideal learned representation should display transferability and robus...
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03/24/2022
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision
Foundation models offer an exciting new paradigm for constructing models...
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03/03/2021
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
Labeling data for modern machine learning is expensive and time-consumin...
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06/26/2020
Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings
Our goal is to enable machine learning systems to be trained interactive...
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02/27/2020
