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Multi-Task Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 461–470 of 3687 papers

Title	Date	Tasks	Status	Hype
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers	Nov 18, 2020	DecoderMulti-Task Learning	CodeCode Available	1
Anomaly Detection in Video via Self-Supervised and Multi-Task Learning	Nov 15, 2020	Abnormal Event Detection In VideoAnomaly Detection	CodeCode Available	1
Context-Aware Answer Extraction in Question Answering	Nov 5, 2020	Multi-Task LearningPrediction	CodeCode Available	1
MTLB-STRUCT @PARSEME 2020: Capturing Unseen Multiword Expressions Using Multi-task Learning and Pre-trained Masked Language Models	Nov 4, 2020	Multi-Task Learning	CodeCode Available	1
Not a cute stroke: Analysis of Rule- and Neural Network-based Information Extraction Systems for Brain Radiology Reports	Nov 1, 2020	Multi-Task LearningNegation	CodeCode Available	1
Ask Your Humans: Using Human Instructions to Improve Generalization in Reinforcement Learning	Nov 1, 2020	Multi-Task Learningreinforcement-learning	CodeCode Available	1
APE: Argument Pair Extraction from Peer Review and Rebuttal via Multi-task Learning	Nov 1, 2020	Argument Pair Extraction (APE)Multi-Task Learning	CodeCode Available	1
Leveraging speaker attribute information using multi task learning for speaker verification and diarization	Oct 27, 2020	AttributeMulti-Task Learning	CodeCode Available	1
Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation	Oct 24, 2020	Knowledge DistillationMachine Translation	CodeCode Available	1
A Frustratingly Easy Approach for Entity and Relation Extraction	Oct 24, 2020	Joint Entity and Relation ExtractionMulti-Task Learning	CodeCode Available	1

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All datasets QM9 Cityscapes test NYUv2 OMNIGLOT CelebA UTKFace wireframe dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PCGrad	∆m%	125.7	—	Unverified
2	CAGrad	∆m%	112.8	—	Unverified
3	IMTL-G	∆m%	77.2	—	Unverified
4	Nash-MTL	∆m%	62	—	Unverified
5	BayesAgg-MTL	∆m%	53.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	mIoU	76.41	—	Unverified
2	Nash-MTL	mIoU	75.41	—	Unverified
3	MultiObjectiveOptimization	mIoU	66.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	Mean IoU	58.14	—	Unverified
2	Nash-MTL	Mean IoU	40.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Gumbel-Matrix Routing	Average Accuracy	93.52	—	Unverified
2	Mixture-of-Experts	Average Accuracy	92.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MGDA-UB	Error	8.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BayesAgg-MTL	delta_m	-2.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LETR	FH	83.3	—	Unverified