A PyTorch Library for Multi-Task Learning

A framework for large scale recommendation algorithms.

Multi-Task Deep Neural Networks for Natural Language Understanding

The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".

🌊HMTL: Hierarchical Multi-Task Learning - A State-of-the-Art neural network model for several NLP tasks based on PyTorch and AllenNLP

[ECCV2022] PETR: Position Embedding Transformation for Multi-View 3D Object Detection & [ICCV2023] PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

MMSA is a unified framework for Multimodal Sentiment Analysis.

PyTorch implementation of multi-task learning architectures, incl. MTI-Net (ECCV2020).

A curated list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. ACM Computing Surveys, 2026.

Reading list of Instruction-tuning. A trend starts from Natrural-Instruction (ACL 2022), FLAN (ICLR 2022) and T0 (ICLR 2022).

Unofficial implementation of "TTNet: Real-time temporal and spatial video analysis of table tennis" (CVPR 2020)

A TensorFlow Keras implementation of "Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts" (KDD 2018)

The implementation of "End-to-End Multi-Task Learning with Attention" [CVPR 2019].

High Accuracy and efficiency multi-task fine-tuning framework for Code LLMs. This work has been accepted by KDD 2024.

TensorFlow Script

Awesome Multitask Learning Resources

Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning

[EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models

BERT for Multitask Learning