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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 1281–1290 of 3687 papers

Title	Date	Tasks	Status	Hype
Composite Learning for Robust and Effective Dense Predictions	Oct 13, 2022	Boundary DetectionDepth Estimation	—Unverified	0
Explanations from Large Language Models Make Small Reasoners Better	Oct 13, 2022	Explanation GenerationIn-Context Learning	—Unverified	0
Understanding Impacts of Task Similarity on Backdoor Attack and Detection	Oct 12, 2022	Backdoor AttackMulti-Task Learning	—Unverified	0
Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysis	Oct 12, 2022	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	1
Task Compass: Scaling Multi-task Pre-training with Task Prefix	Oct 12, 2022	Common Sense ReasoningData Augmentation	CodeCode Available	1
Optimizing Evaluation Metrics for Multi-Task Learning via the Alternating Direction Method of Multipliers	Oct 12, 2022	Multi-Task Learning	—Unverified	0
Entity Tracking via Effective Use of Multi-Task Learning Model and Mention-guided Decoding	Oct 12, 2022	Multi-Task LearningTransfer Learning	CodeCode Available	0
Semantic Cross Attention for Few-shot Learning	Oct 12, 2022	Few-Shot Learningimage-classification	CodeCode Available	0
Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approach	Oct 11, 2022	Domain AdaptationMulti-Task Learning	CodeCode Available	1
TriangleNet: Edge Prior Augmented Network for Semantic Segmentation through Cross-Task Consistency	Oct 11, 2022	Autonomous DrivingEdge Detection	CodeCode Available	0

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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