Pinned Repositories
low-resource-text-classification-framework
Research framework for low resource text classification that allows the user to experiment with classification models and active learning strategies on a large number of sentence classification datasets, and to simulate real-world scenarios. The framework is easily expandable to new classification models, active learning strategies and datasets.
quality-controlled-paraphrase-generation
Quality Controlled Paraphrase Generation (ACL 2022)
tutEval
Tutorial on LLM Evaluation in LREC
auto-contrastive-generation
Text generation using language models with multiple exit heads
intermediate-training-using-clustering
code for the paper "Cluster & Tune: Boost Cold Start Performance in Text Classification" for ACL2022
low-resource-text-classification-framework
Research framework for low resource text classification that allows the user to experiment with classification models and active learning strategies on a large number of sentence classification datasets, and to simulate real-world scenarios. The framework is easily expandable to new classification models, active learning strategies and datasets.
unitxt
🦄 Unitxt: a python library for getting data fired up and set for training and evaluation
zero-shot-classification-boost-with-self-training
code for the paper "Zero-Shot Text Classification with Self-Training" for EMNLP 2022
label-sleuth
Open source no-code system for text annotation and building of text classifiers
label-sleuth.org
The official website of Label Sleuth
arielge's Repositories
arielge/low-resource-text-classification-framework
Research framework for low resource text classification that allows the user to experiment with classification models and active learning strategies on a large number of sentence classification datasets, and to simulate real-world scenarios. The framework is easily expandable to new classification models, active learning strategies and datasets.
arielge/quality-controlled-paraphrase-generation
Quality Controlled Paraphrase Generation (ACL 2022)