Multi-Task Deep Neural Networks for Natural Language Understanding
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Updated
Mar 20, 2023 - Python
Multi-Task Deep Neural Networks for Natural Language Understanding
A framework for large scale recommendation algorithms.
A PyTorch Library for Multi-Task Learning
The implementation of "Prismer: A Vision-Language Model with An Ensemble of Experts".
TensorFlow Script
A TensorFlow Keras implementation of "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" (KDD 2018)
PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).
Awesome Multitask Learning Resources
The implementation of "End-to-End Multi-Task Learning with Attention" [CVPR 2019].
BERT for Multitask Learning
[ECCV2022] PETR: Position Embedding Transformation for Multi-View 3D Object Detection
Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)
Problem Agnostic Speech Encoder
[EMNLP 2022] A Unified Framework and Analysis for Structured Knowledge Grounding with Text-to-Text Language Models
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning
2023 up-to-date list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.
Live Training for Open-source Big Models
MMSA is a unified framework for Multimodal Sentiment Analysis.
Deep Recommenders
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