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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

Showing 251300 of 3687 papers

TitleStatusHype
GaitFormer: Learning Gait Representations with Noisy Multi-Task LearningCode1
DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of ExpertsCode1
MetaBEV: Solving Sensor Failures for BEV Detection and Map SegmentationCode1
MetaICL: Learning to Learn In ContextCode1
AutoMTL: A Programming Framework for Automating Efficient Multi-Task LearningCode1
Automatic Charge Identification from Facts: A Few Sentence-Level Charge Annotations is All You NeedCode1
AV-RIR: Audio-Visual Room Impulse Response EstimationCode1
Florence-2: Advancing a Unified Representation for a Variety of Vision TasksCode1
Auto-Lambda: Disentangling Dynamic Task RelationshipsCode1
FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security AnalysisCode1
Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task ArithmeticCode1
Aggression and Misogyny Detection using BERT: A Multi-Task ApproachCode1
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian RegularizationCode1
Few-shot Knowledge Graph-to-Text Generation with Pretrained Language ModelsCode1
Flexible Style Image Super-Resolution using Conditional ObjectiveCode1
A Simple and Efficient Multi-Task Learning Approach for Conditioned Dialogue GenerationCode1
Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual ModelsCode1
Feature Decomposition for Reducing Negative Transfer: A Novel Multi-task Learning Method for Recommender SystemCode1
Fair Resource Allocation in Multi-Task LearningCode1
FedCL: Federated Multi-Phase Curriculum Learning to Synchronously Correlate User HeterogeneityCode1
Exploring Correlations of Self-Supervised Tasks for GraphsCode1
Evaluating Logical Generalization in Graph Neural NetworksCode1
Explain and Predict, and then Predict AgainCode1
Ditto: Fair and Robust Federated Learning Through PersonalizationCode1
ENHANCE (ENriching Health data by ANnotations of Crowd and Experts): A case study for skin lesion classificationCode1
End-to-End Real-World Polyphonic Piano Audio-to-Score Transcription with Hierarchical DecodingCode1
Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task LearningCode1
End-to-end Emotion-Cause Pair Extraction via Learning to LinkCode1
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft PromptsCode1
Evidentiality-guided Generation for Knowledge-Intensive NLP TasksCode1
Exploiting Learnable Joint Groups for Hand Pose EstimationCode1
Exploiting Shared Representations for Personalized Federated LearningCode1
EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNINGCode1
Extraction of cropland field parcels with high resolution remote sensing using multi-task learningCode1
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal LearningCode1
End-to-End Multi-Task Learning with AttentionCode1
A generic physics-informed neural network-based framework for reliability assessment of multi-state systemsCode1
A Unified Object Motion and Affinity Model for Online Multi-Object TrackingCode1
An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment AnalysisCode1
An Investigation of End-to-End Models for Robust Speech RecognitionCode1
FiLM-Ensemble: Probabilistic Deep Learning via Feature-wise Linear ModulationCode1
A Unified Span-Based Approach for Opinion Mining with Syntactic ConstituentsCode1
A Gradually Soft Multi-Task and Data-Augmented Approach to Medical Question UnderstandingCode1
Annotating Columns with Pre-trained Language ModelsCode1
Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial TrainingCode1
Empirical Bayes Transductive Meta-Learning with Synthetic GradientsCode1
Automatic Severity Classification of Dysarthric speech by using Self-supervised Model with Multi-task LearningCode1
Anomaly Detection in Video via Self-Supervised and Multi-Task LearningCode1
Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic EnvironmentsCode1
Emotion-Cause Pair Extraction: A New Task to Emotion Analysis in TextsCode1
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Benchmark Results

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