Self-Guided Contrastive Learning for BERT Sentence Representations

Last update: Dec 04, 2022

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Overview

Self-Guided Contrastive Learning for BERT Sentence Representations

This repository is dedicated for releasing the implementation of the models utilized in the paper named Self-Guided Contrastive Learning for BERT Sentence Representations (ACL 21).

Unfortunately, I'm still on the way of polishing my code for making it public.

Please stay tuned for update!

Thank you.

Owner

Taeuk Kim

Assistant Professor at Hanyang University. B.S. & Ph.D. at Seoul National University. Research Interests: NLP, Machine Learning, Deep Learning

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Self-Guided Contrastive Learning for BERT Sentence Representations

Related tags

Overview

Self-Guided Contrastive Learning for BERT Sentence Representations

Owner

Taeuk Kim

a dnn ai project to classify which food people are eating on audio recordings

YOLOv5 in PyTorch > ONNX > CoreML > TFLite

fklearn: Functional Machine Learning

MG-GCN: Scalable Multi-GPU GCN Training Framework

Running Google MoveNet Multipose Tracking models on OpenVINO.

Keras attention models including botnet,CoaT,CoAtNet,CMT,cotnet,halonet,resnest,resnext,resnetd,volo,mlp-mixer,resmlp,gmlp,levit

imbalanced-DL: Deep Imbalanced Learning in Python

Few-Shot Object Detection via Association and DIscrimination

Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

This repo is about to create the Streamlit application for given ML model.

FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks

Library for fast text representation and classification.

FairMOT - A simple baseline for one-shot multi-object tracking

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