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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 951–1000 of 3687 papers

TitleStatusHype
Extractive Summarization Using Multi-Task Learning with Document Classification—0
Facial expression and attributes recognition based on multi-task learning of lightweight neural networks—0
DynaShare: Task and Instance Conditioned Parameter Sharing for Multi-Task Learning—0
E2E-based Multi-task Learning Approach to Joint Speech and Accent Recognition—0
Feature Partitioning for Efficient Multi-Task Architectures—0
融合多任務學習類神經網路聲學模型訓練於會議語音辨識之研究 (Leveraging Multi-Task Learning with Neural Network Based Acoustic Modeling for Improved Meeting Speech Recognition) [In Chinese]—0
Domain-Agnostic Few-Shot Classification by Learning Disparate Modulators—0
Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning—0
GEmo-CLAP: Gender-Attribute-Enhanced Contrastive Language-Audio Pretraining for Accurate Speech Emotion Recognition—0
ECNU: Using Traditional Similarity Measurements and Word Embedding for Semantic Textual Similarity Estimation—0
ECRC: Emotion-Causality Recognition in Korean Conversation for GCN—0
Deep Learning based Positioning with Multi-task Learning and Uncertainty-based Fusion—0
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection—0
Edinburgh’s End-to-End Multilingual Speech Translation System for IWSLT 2021—0
EEGEncoder: Advancing BCI with Transformer-Based Motor Imagery Classification—0
EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification—0
Deep Learning Approach for Matrix Completion Using Manifold Learning—0
Effective Adaptation in Multi-Task Co-Training for Unified Autonomous Driving—0
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks—0
Effects of Word-frequency based Pre- and Post- Processings for Audio Captioning—0
Efficient Action Detection in Untrimmed Videos via Multi-Task Learning—0
Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging—0
Deep Latent Emotion Network for Multi-Task Learning—0
Efficient and Scalable Multi-task Regression on Massive Number of Tasks—0
Boosting Facial Action Unit Detection Through Jointly Learning Facial Landmark Detection and Domain Separation and Reconstruction—0
Deep Joint Source-Channel Coding for Multi-Task Network—0
Audio-Visual Fusion Layers for Event Type Aware Video Recognition—0
Efficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation—0
A deep latent variable model for semi-supervised multi-unit soft sensing in industrial processes—0
DeepHider: A Covert NLP Watermarking Framework Based on Multi-task Learning—0
Efficient Image Gallery Representations at Scale Through Multi-Task Learning—0
Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening—0
Deep generative model-driven multimodal prostate segmentation in radiotherapy—0
Efficient Low-Resolution Face Recognition via Bridge Distillation—0
Efficiently Identifying Task Groupings for Multi-Task Learning—0
Efficient Meta Lifelong-Learning with Limited Memory—0
BoundMatch: Boundary detection applied to semi-supervised segmentation for urban-driving scenes—0
Analyzing the Effect of Multi-task Learning for Biomedical Named Entity Recognition—0
Bounds for Vector-Valued Function Estimation—0
Efficient Multi-task Prompt Tuning for Recommendation—0
Efficient Multi-task Uncertainties for Joint Semantic Segmentation and Monocular Depth Estimation—0
Efficient Output Kernel Learning for Multiple Tasks—0
Efficient Pairwise Learning Using Kernel Ridge Regression: an Exact Two-Step Method—0
Efficient Pareto Manifold Learning with Low-Rank Structure—0
Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning—0
Brain Hematoma Marker Recognition Using Multitask Learning: SwinTransformer and Swin-Unet—0
Efficient Residual Learning with Mixture-of-Experts for Universal Dexterous Grasping—0
Efficient Retrieval Optimized Multi-task Learning—0
DeepGeneMD: A Joint Deep Learning Model for Extracting Gene Mutation-Disease Knowledge from PubMed Literature—0
Audio Tagging by Cross Filtering Noisy Labels—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