SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2576–2600 of 3687 papers

TitleStatusHype
Object Semantics Give Us the Depth We Need: Multi-task Approach to Aerial Depth Completion—0
OccuSeg: Occupancy-aware 3D Instance Segmentation—0
OCELOT: Overlapped Cell on Tissue Dataset for Histopathology—0
OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction—0
A New Representation of Skeleton Sequences for 3D Action Recognition—0
Off-the-Shelf Unsupervised NMT—0
A New Benchmark of Aphasia Speech Recognition and Detection Based on E-Branchformer and Multi-task Learning—0
OmniArt: Multi-task Deep Learning for Artistic Data Analysis—0
OmniDialog: An Omnipotent Pre-training Model for Task-Oriented Dialogue System—0
Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning—0
Channel Type Recognition in Wireless Communications: A Deep Learning Approach—0
A Neural Transition-based Joint Model for Disease Named Entity Recognition and Normalization—0
On Better Exploring and Exploiting Task Relationships in Multi-Task Learning: Joint Model and Feature Learning—0
OneDiff: A Generalist Model for Image Difference Captioning—0
One General Teacher for Multi-Data Multi-Task: A New Knowledge Distillation Framework for Discourse Relation Analysis—0
A neural joint model for Vietnamese word segmentation, POS tagging and dependency parsing—0
SkillNet-NLU: A Sparsely Activated Model for General-Purpose Natural Language Understanding—0
One Model To Learn Them All—0
One "Ruler" for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning—0
One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets—0
One Shot Joint Colocalization and Cosegmentation—0
One Size Fits All? A simple LSTM for non-literal token and construction-level classification—0
One-stage Modality Distillation for Incomplete Multimodal Learning—0
An Entailment Tree Generation Approach for Multimodal Multi-Hop Question Answering with Mixture-of-Experts and Iterative Feedback Mechanism—0
An Ensemble Method to Automatically Grade Diabetic Retinopathy with Optical Coherence Tomography Angiography Images—0
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All datasetsQM9Cityscapes testNYUv2OMNIGLOTCelebAUTKFacewireframe dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PCGrad∆m%125.7—Unverified
2CAGrad∆m%112.8—Unverified
3IMTL-G∆m%77.2—Unverified
4Nash-MTL∆m%62—Unverified
5BayesAgg-MTL∆m%53.7—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLmIoU76.41—Unverified
2Nash-MTLmIoU75.41—Unverified
3MultiObjectiveOptimizationmIoU66.63—Unverified
#ModelMetricClaimedVerifiedStatus
1SwinMTLMean IoU58.14—Unverified
2Nash-MTLMean IoU40.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Gumbel-Matrix RoutingAverage Accuracy93.52—Unverified
2Mixture-of-ExpertsAverage Accuracy92.19—Unverified
#ModelMetricClaimedVerifiedStatus
1MGDA-UBError8.25—Unverified
#ModelMetricClaimedVerifiedStatus
1BayesAgg-MTLdelta_m-2.23—Unverified
#ModelMetricClaimedVerifiedStatus
1LETRFH83.3—Unverified