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 3401–3425 of 3687 papers

TitleStatusHype
EF-LLM: Energy Forecasting LLM with AI-assisted Automation, Enhanced Sparse Prediction, Hallucination Detection—0
Egocentric Audio-Visual Noise Suppression—0
Egocentric Video Task Translation—0
CUHK at SemEval-2020 Task 4: CommonSense Explanation, Reasoning and Prediction with Multi-task Learning—0
Electricity Demand Forecasting by Multi-Task Learning—0
Stepback: Enhanced Disentanglement for Voice Conversion via Multi-Task Learning—0
Elite360M: Efficient 360 Multi-task Learning via Bi-projection Fusion and Cross-task Collaboration—0
CS-UM6P at SemEval-2021 Task 7: Deep Multi-Task Learning Model for Detecting and Rating Humor and Offense—0
Multitask Kernel-based Learning with First-Order Logic Constraints—0
Embedding Label Structures for Fine-Grained Feature Representation—0
Embedding Structured Dictionary Entries—0
Embedding Time Differences in Context-sensitive Neural Networks for Learning Time to Event—0
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation—0
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems—0
A Brief Review of Deep Multi-task Learning and Auxiliary Task Learning—0
Crude Oil-related Events Extraction and Processing: A Transfer Learning Approach—0
Emotion Detection and Classification in a Multigenre Corpus with Joint Multi-Task Deep Learning—0
An SCMA Receiver for 6G NTN based on Multi-Task Learning—0
Stochastic DCA for minimizing a large sum of DC functions with application to Multi-class Logistic Regression—0
Emotion Recognition with Incomplete Labels Using Modified Multi-task Learning Technique—0
Cross-topic Argument Mining from Heterogeneous Sources—0
Employing the Correspondence of Relations and Connectives to Identify Implicit Discourse Relations via Label Embeddings—0
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels—0
Emu Edit: Precise Image Editing via Recognition and Generation Tasks—0
Enabling Asymmetric Knowledge Transfer in Multi-Task Learning with Self-Auxiliaries—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