The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
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Updated
Oct 23, 2024 - Python
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
A system for quickly generating training data with weak supervision
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
skweak: A software toolkit for weak supervision applied to NLP tasks
BOND: BERT-Assisted Open-Domain Name Entity Recognition with Distant Supervision
Labelling platform for text using weak supervision.
[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark
Manga&Comic text detection
[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.
Implementation of CRAFT Text Detection
A curated list of programmatic weak supervision papers and resources
Self-training with Weak Supervision (NAACL 2021)
Labeling is boring. Use this tool to speed up your next object detection project!
Weakly Supervised End-to-End Learning (NeurIPS 2021)
Dataset for paper "Weak Supervision for Fake News Detection via Reinforcement Learning" published in AAAI'2020.
Framework to learn Named Entity Recognition models without labelled data using weak supervision.
A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
SPEAR: Programmatically label and build training data quickly.
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
Weakly supervised medical named entity classification
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