awesome-multi-task-learning
A curated list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.
https://github.com/thuml/awesome-multi-task-learning
Last synced: 8 days ago
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Benchmark & Dataset
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Graph
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NLP
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Recommendation
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RL & Robotics
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Codebase
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Recommendation
- MTReclib - task recommendation models and common datasets.
- LibMTL - Task Learning
- MALSAR - task learning via Structural Regularization (⚠️ Non-deep Learning)
- Multi-Task-Learning-PyTorch - task learning architectures
- mtan - to-End Multi-Task Learning with Attention"
- auto-lambda - Lambda: Disentangling Dynamic Task Relationships"
- astmt - tasking of Multiple Tasks
- mt-dnn - Task Deep Neural Networks for Natural Language Understanding
- mtrl
- TorchJD - task learning).
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Misc
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Consistency
- 12-in-1: Multi-Task Vision and Language Representation Learning
- What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
- Multitask Learning Strengthens Adversarial Robustness
- Multi-Task Adversarial Attack
- BAM! Born-Again Multi-Task Networks for Natural Language Understanding
- Tasks Without Borders: A New Approach to Online Multi-Task Learning
- Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains
- Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back
- Unifying and Merging Well-trained Deep Neural Networks for Inference Stage - ECAI, 2018.
- Federated Multi-Task Learning
- Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives
- A Unified Perspective on Multi-Domain and Multi-Task Learning
- BAM! Born-Again Multi-Task Networks for Natural Language Understanding
- MultiMAE: Multi-modal Multi-task Masked Autoencoders
- What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
- Multi-task Self-Supervised Visual Learning
- One Model To Learn Them All
- Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives
- A Unified Perspective on Multi-Domain and Multi-Task Learning
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Optimization
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Adversarial Training
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Consistency
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Distillation
- Universal Representations: A Unified Look at Multiple Task and Domain Learning
- Multi-Task Self-Training for Learning General Representations
- Knowledge Distillation for Multi-task Learning - Workshop, 2020.
- Distral: Robust Multitask Reinforcement Learning
- Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning
- Policy Distillation
- Multi-Task Self-Training for Learning General Representations
- Knowledge Distillation for Multi-task Learning - Workshop, 2020.
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Loss & Gradient Strategy
- MGDA
- Nash-MTL
- Population-Based Training
- Aligned-MTL
- MoCo
- FAMO
- AuxiNash
- Do Current Multi-Task Optimization Methods in Deep Learning Even Help?
- Unitary Scalarization
- Auto-λ
- Rotograd
- RLW / RGW
- PINNsNTK
- Inverse-Dirichlet PINNs
- CAGrad
- Gradient Vaccine
- IMTL
- GradientPathologiesPINNs
- IT-MTL
- GradDrop
- Online Learning for Auxiliary losses (OL-AUX)
- PopArt
- Learning values across many orders of magnitude
- Geometric Loss Strategy (GLS)
- LBTW
- Gradient Cosine Similarity
- Revised Uncertainty
- GradNorm
- Dynamic Task Prioritization
- Uncertainty
- AdaLoss
- Task-wise Early Stopping
- FairGrad
- SDMGrad
- FS-MTL
- UPGrad
- ConFIG
- IGB
- FAMO
- ForkMerge
- Unitary Scalarization
- Auto-λ
- Rotograd
- RLW / RGW
- Revised Uncertainty
- AdaLoss
- PopArt
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Pareto
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Task Interference
- A Modulation Module for Multi-task Learning with Applications in Image Retrieval
- On Negative Interference in Multilingual Models: Findings and A Meta-Learning Treatment
- Ray Interference: A Source of Plateaus in Deep Reinforcement Learning
- On Negative Interference in Multilingual Models: Findings and A Meta-Learning Treatment
- Ray Interference: A Source of Plateaus in Deep Reinforcement Learning
- Dataless Weight Disentanglement in Task Arithmetic via Kronecker-Factored Approximate Curvature
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Task Sampling
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Survey
- Multi-Task Learning for Dense Prediction Tasks: A Survey
- Multi-Task Learning with Deep Neural Networks: A Survey
- Multi-task learning for natural language processing in the 2020s: Where are we going?
- A Comparison of Loss Weighting Strategies for Multi task Learning in Deep Neural Networks
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- A Survey on Multi-Task Learning
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
- Empirical Evaluation of Multi-task Learning in Deep Neural Networks for Natural Language Processing
Categories
Sub Categories
Hard Parameter Sharing
85
Graph
63
Consistency
58
Loss & Gradient Strategy
47
Modularity, MoE, Routing & NAS
26
Modulation & Adapters
21
Computer Vision
14
Recommendation
14
Others
8
Soft Parameter Sharing
8
Distillation
8
Task Interference
6
Pareto
4
NLP
4
Adversarial Training
4
Decoder-focused Model
4
Task Sampling
3
RL & Robotics
2
Keywords
multi-task-learning
7
pytorch
5
deep-learning
4
multitask-learning
4
meta-learning
2
python
2
multiobjective-optimization
2
multi-objective-optimization
2
nlp
2
segmentation
1
auxiliary-learning
1
attention-model
1
natural-language-processing
1
benchmark
1
bigbench
1
crossfit
1
curated-datasets
1
dataset-collection
1
discriminative
1
scene-understanding
1
pascal
1
nyud
1
eccv2020
1
computer-vision
1
ranking
1
natural-language-understanding
1
named-entity-recognition
1
microsoft
1
machine-reading-comprehension
1
torch
1
optimization
1
jacobian-descent
1
multi-task-clustering
1
matlab
1
ple
1
multi-domain-learning
1
mtl
1
mmoe
1
transfer-learning
1
recommender-system
1
recommendation
1
multitask-recommendation
1
ctr-prediction
1
advertising
1
text-classification
1
scaling
1
reward-modeling
1
preprocessings
1
natural-language-inference
1
multi-task-learning-scaling
1