A curated list of pretrained sentence and word embedding models

AI ChatBot using Python Tensorflow and Natural Language Processing (NLP) along side TFLearn

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

Code for the paper "Contextualized Weak Supervision for Text Classification"

Arabic NER system with a strong performance

Official implementation of DenoMamba: A fused state-space model for low-dose CT denoising

Code for "Let's Stop Incorrect Comparisons in End-to-end Relation Extraction!", EMNLP 2020

Code for "Contextualized Embeddings in Named-Entity Recognition", ECIR 2020

😷 The Fill-Mask Association Test (FMAT): Measuring Propositions in Natural Language.

The official repo for the EACL 2023 paper "Quantifying Context Mixing in Transformers"

Implementation of GAP: Graph Neighborhood Attentive Pooling, https://arxiv.org/abs/2001.10394. A context-sensitve graph (network) representation learning algorithm that relies only on the structure of the graph.

Jointly Learning knowledge graph Embedding, Fine Grain Entity Types and Language Modeling.

This project explores both Transfer Learning and Feature Extraction for obtaining contextual word embeddings using BERT-family model to solve a problem related to the Fake News Detection task, i.e. Stance Detection.

FuseMap: Integrate spatial transcripomics with universal gene, cell, and tissue embeddings.

Software -> Hardware for performance; Hardware -> Software for robustness;