IBM / low-resource-text-classification-frameworkLinks
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.
☆101Updated 3 years ago
Alternatives and similar repositories for low-resource-text-classification-framework
Users that are interested in low-resource-text-classification-framework are comparing it to the libraries listed below
Sorting:
- Collection of NLP model explanations and accompanying analysis tools☆144Updated 2 years ago
- ☆87Updated 3 years ago
- https://arxiv.org/pdf/1909.04054☆79Updated 2 years ago
- [NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self…☆203Updated 2 years ago
- Data/Code Repository for https://api.semanticscholar.org/CorpusID:218470122☆135Updated last year
- ☆120Updated 5 years ago
- State of the art Semantic Sentence Embeddings☆99Updated 3 years ago
- ☆68Updated 3 months ago
- SUPERT: Unsupervised multi-document summarization evaluation & generation☆94Updated 2 years ago
- Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling☆46Updated 5 years ago
- Framework for weakly supervised deep sequence taggers, focused on named entity recognition☆78Updated 2 years ago
- Source code for paper "Learning from Noisy Labels for Entity-Centric Information Extraction", EMNLP 2021☆55Updated 3 years ago
- Interpretable Evaluation for (Almost) All NLP Tasks☆195Updated 2 years ago
- Pytorch implementation of Highly Parallel Autoregressive Entity Linking with Discriminative Correction☆67Updated 3 years ago
- ☆36Updated 2 years ago
- A library to conduct ranking experiments with transformers.☆159Updated 2 years ago
- Evaluation script for named entity recognition (NER) systems based on entity-level F1 score.☆69Updated 4 years ago
- Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data☆100Updated 2 years ago
- Framework to learn Named Entity Recognition models without labelled data using weak supervision.☆123Updated 4 years ago
- A Natural Language Inference (NLI) model based on Transformers (BERT and ALBERT)☆132Updated last year
- Automatically detect errors in annotated corpora.☆47Updated last year
- Self-supervised NER prototype - updated version (69 entity types - 17 broad entity groups). Uses pretrained BERT models with no fine tuni…☆78Updated 3 years ago
- Multi^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT (Findings of ACL: EMNLP 2020)☆56Updated 2 years ago
- [EMNLP 2021] Improving and Simplifying Pattern Exploiting Training☆153Updated 3 years ago
- BOND: BERT-Assisted Open-Domain Name Entity Recognition with Distant Supervision☆290Updated 4 years ago
- CrossWeigh: Training Named Entity Tagger from Imperfect Annotations☆177Updated last year
- Master thesis with code investigating methods for incorporating long-context reasoning in low-resource languages, without the need to pre…☆33Updated 3 years ago
- On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines☆137Updated last year
- Annotated corpus and code for "Extracting COVID-19 Events from Twitter".☆44Updated 3 years ago
- pyTorch implementation of Recurrence over BERT (RoBERT) based on this paper https://arxiv.org/abs/1910.10781 and comparison with pyTorch …☆82Updated 2 years ago