weak-supervision

Cleanlab's open-source library is 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

Manga&Comic text detection

BOND: BERT-Assisted Open-Domain Name Entity Recognition with Distant Supervision

Labelling platform for text using weak supervision.

[NeurIPS 2021] WRENCH: Weak supeRvision bENCHmark

[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.

A curated list of programmatic weak supervision papers and resources

Implementation of CRAFT Text Detection

Official implementation of SuperSimpleNet [ICPR 2024, JIMS 2025]

Labeling is boring. Use this tool to speed up your next object detection project!

Self-training with Weak Supervision (NAACL 2021)

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.

SPEAR: Programmatically label and build training data quickly.

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.

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data