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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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 526–550 of 3687 papers

TitleStatusHype
MTDT: A Multi-Task Deep Learning Digital Twin—0
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-ExpertsCode3
Multi-task Learning-based Joint CSI Prediction and Predictive Transmitter Selection for Security—0
Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model ErasCode2
Open-Set Video-based Facial Expression Recognition with Human Expression-sensitive Prompting—0
OmniSearchSage: Multi-Task Multi-Entity Embeddings for Pinterest SearchCode2
Mixed Supervised Graph Contrastive Learning for Recommendation—0
EEGEncoder: Advancing BCI with Transformer-Based Motor Imagery Classification—0
Narrative Action Evaluation with Prompt-Guided Multimodal InteractionCode1
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of ExpertsCode3
Machine Learning-Assisted Thermoelectric Cooling for On-Demand Multi-Hotspot Thermal Management—0
Text-dependent Speaker Verification (TdSV) Challenge 2024: Challenge Evaluation Plan—0
An Offline Reinforcement Learning Algorithm Customized for Multi-Task Fusion in Large-Scale Recommender Systems—0
A Point-Based Approach to Efficient LiDAR Multi-Task Perception—0
TIMIT Speaker Profiling: A Comparison of Multi-task learning and Single-task learning Approaches—0
Physical formula enhanced multi-task learning for pharmacokinetics prediction—0
MOWA: Multiple-in-One Image Warping Model—0
Integrating knowledge bases to improve coreference and bridging resolution for the chemical domain—0
Negation Triplet Extraction with Syntactic Dependency and Semantic ConsistencyCode0
DKE-Research at SemEval-2024 Task 2: Incorporating Data Augmentation with Generative Models and Biomedical Knowledge to Enhance Inference Robustness—0
Navigating the Landscape of Large Language Models: A Comprehensive Review and Analysis of Paradigms and Fine-Tuning StrategiesCode0
MING-MOE: Enhancing Medical Multi-Task Learning in Large Language Models with Sparse Mixture of Low-Rank Adapter ExpertsCode5
Enhancing Fairness and Performance in Machine Learning Models: A Multi-Task Learning Approach with Monte-Carlo Dropout and Pareto Optimality—0
FedAuxHMTL: Federated Auxiliary Hard-Parameter Sharing Multi-Task Learning for Network Edge Traffic Classification—0
Structure-aware Fine-tuning for Code Pre-trained Models—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