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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 261–270 of 3687 papers

Title	Date	Tasks	Status	Hype
Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approach	Oct 11, 2022	Domain AdaptationMulti-Task Learning	CodeCode Available	1
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation	Oct 8, 2022	DecoderGraph Neural Network	CodeCode Available	1
Causal Inference for Chatting Handoff	Oct 6, 2022	Causal InferenceChatbot	CodeCode Available	1
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control	Oct 5, 2022	Imitation LearningMulti-Task Learning	CodeCode Available	1
CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning	Oct 3, 2022	AllMulti-Task Learning	CodeCode Available	1
Neural Graphical Models	Oct 2, 2022	Multi-Task Learning	CodeCode Available	1
Logical Form Generation via Multi-task Learning for Complex Question Answering over Knowledge Bases	Oct 1, 2022	Entity DisambiguationForm	CodeCode Available	1
MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference	Sep 28, 2022	Collaborative InferenceDeep Reinforcement Learning	CodeCode Available	1
Mind the Gap! Injecting Commonsense Knowledge for Abstractive Dialogue Summarization	Sep 2, 2022	Abstractive Dialogue SummarizationMulti-Task Learning	CodeCode Available	1
Retinal Structure Detection in OCTA Image via Voting-based Multi-task Learning	Aug 23, 2022	ClassificationDecision Making	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