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Found 5 papers, 3 papers with code
Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning
Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult.
Cross-Geography Generalization of Machine Learning Methods for Classification of Flooded Regions in Aerial Images
This work proposes two approaches for identifying flooded regions in UAV aerial images.
A general-purpose material property data extraction pipeline from large polymer corpora using Natural Language Processing
The ever-increasing number of materials science articles makes it hard to infer chemistry-structure-property relations from published literature.
PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning
Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult.
BERTifying the Hidden Markov Model for Multi-Source Weakly Supervised Named Entity Recognition
To address this challenge, we propose a conditional hidden Markov model (CHMM), which can effectively infer true labels from multi-source noisy labels in an unsupervised way.
