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

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Showing 2451–2475 of 3687 papers

TitleStatusHype
IDE-Net: Interactive Driving Event and Pattern Extraction from Human Data—0
Multi-Task Learning for Calorie Prediction on a Novel Large-Scale Recipe Dataset Enriched with Nutritional Information—0
Translation Quality Estimation by Jointly Learning to Score and Rank—0
How Far Can We Go with Data Selection? A Case Study on Semantic Sequence Tagging Tasks—0
The University of Helsinki and Aalto University submissions to the WMT 2020 news and low-resource translation tasks—0
The NiuTrans System for the WMT20 Quality Estimation Shared Task—0
TEST_POSITIVE at W-NUT 2020 Shared Task-3: Cross-task modeling—0
Embedding Structured Dictionary Entries—0
Advancing Seq2seq with Joint Paraphrase Learning—0
Multi-Task Learning using Dynamic Task Weighting for Conversational Question Answering—0
Coupled Hierarchical Transformer for Stance-Aware Rumor Verification in Social Media Conversations—0
Analyzing the Effect of Multi-task Learning for Biomedical Named Entity Recognition—0
Zero-Shot Rationalization by Multi-Task Transfer Learning from Question AnsweringCode0
STANDER: An Expert-Annotated Dataset for News Stance Detection and Evidence RetrievalCode0
Biomedical Event Extraction as Sequence Labeling—0
Exploring Logically Dependent Multi-task Learning with Causal Inference—0
Simple Hierarchical Multi-Task Neural End-To-End Entity Linking for Biomedical Text—0
LIMIT-BERT : Linguistics Informed Multi-Task BERTCode0
Enhancing Automated Essay Scoring Performance via Fine-tuning Pre-trained Language Models with Combination of Regression and Ranking—0
Response Selection for Multi-Party Conversations with Dynamic Topic Tracking—0
Towards Enhancing Faithfulness for Neural Machine Translation—0
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender SystemCode0
PAL : Pretext-based Active Learning—0
Measuring and Harnessing Transference in Multi-Task Learning—0
Finite-Time Convergence Rates of Decentralized Stochastic Approximation with Applications in Multi-Agent and Multi-Task Learning—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