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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

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Showing 526–550 of 3687 papers

TitleStatusHype
An Empirical Study of Multi-Task Learning on BERT for Biomedical Text MiningCode1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
Compressed Context Memory For Online Language Model InteractionCode1
An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure SystemsCode1
Causal Inference for Chatting HandoffCode1
Instruction Tuning for Few-Shot Aspect-Based Sentiment AnalysisCode1
Language Models are Unsupervised Multitask LearnersCode1
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language ModelsCode1
Compressed Interaction Graph based Framework for Multi-behavior RecommendationCode1
CentralNet: a Multilayer Approach for Multimodal FusionCode1
CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task LearningCode1
LEAF: A Benchmark for Federated SettingsCode1
Learning Class-Transductive Intent Representations for Zero-shot Intent DetectionCode1
A Frustratingly Easy Approach for Entity and Relation ExtractionCode1
Context-Aware Answer Extraction in Question AnsweringCode1
An End-to-End Multi-Task Learning Model for Image-based Table RecognitionCode1
Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment AnalysisCode1
An End-to-End Progressive Multi-Task Learning Framework for Medical Named Entity Recognition and NormalizationCode1
Continued Pretraining for Better Zero- and Few-Shot PromptabilityCode1
AdaMerging: Adaptive Model Merging for Multi-Task LearningCode1
Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task IntegrationCode1
CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of ModalityCode1
CIF: Continuous Integrate-and-Fire for End-to-End Speech RecognitionCode1
Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry ConstraintsCode1
Continual Learning in Task-Oriented Dialogue SystemsCode1
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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