Multi Task Learning

Multi-task learning (MTL) aims to improve model efficiency and generalization by training a single model to perform multiple related tasks simultaneously. Current research focuses on addressing challenges like task interference and optimization difficulties, exploring architectures such as Mixture-of-Experts (MoE), low-rank adaptors, and hierarchical models to enhance performance and efficiency across diverse tasks. MTL's significance lies in its potential to improve resource utilization and create more robust and adaptable AI systems, with applications spanning various fields including natural language processing, computer vision, and scientific modeling.

Papers

November 22, 2022

Mitigating Negative Transfer in Multi-Task Learning with Exponential Moving Average Loss Weighting Strategies
Anish Lakkapragada, Essam Sleiman, Saimourya Surabhi, Dennis P. Wall
Deep Learning Multi Task Learning Single Task Adaptive Loss Balanced Loss Negative Transfer

November 21, 2022

November 20, 2022

UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning
Zengzhi Wang, Rui Xia, Jianfei Yu
Multi Task Learning Aspect Based Sentiment Analysis Task Specific Model

November 18, 2022

November 14, 2022

MT4SSL: Boosting Self-Supervised Speech Representation Learning by Integrating Multiple Targets
Ziyang Ma, Zhisheng Zheng, Changli Tang, Yujin Wang, Xie Chen
Self Supervised Learning Multi Task Learning Self Supervised Speech Model Multi Task Learning Framework Multiple Target Self Supervised Speech Representation Learning

November 11, 2022

November 6, 2022

Preserving background sound in noise-robust voice conversion via multi-task learning
Jixun Yao, Yi Lei, Qing Wang, Pengcheng Guo, Ziqian Ning, Lei Xie, Hai Li, Junhui Liu, Danming Xie
Multi Task Learning Source Separation Separation Model Background Sound

November 2, 2022

Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring
Arka Daw, Kyongmin Yeo, Anuj Karpatne, Levente Klein
Multi Task Learning Source Attribution Field Reconstruction Dispersion Profile Sparse Measurement Methane Source Methane Emission Methane Flux

October 31, 2022

Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5
Irina Bigoulaeva, Rachneet Sachdeva, Harish Tayyar Madabushi, Aline Villavicencio, Iryna Gurevych
Fine Tuning Multi Task Learning Natural Language Inference T5 Model Cross Task Knowledge Sequential Multi Task Learning

October 27, 2022

October 26, 2022

October 23, 2022

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach
Heshan Fernando, Han Shen, Miao Liu, Subhajit Chaudhury, Keerthiram Murugesan, Tianyi Chen
Multi Task Learning Multi Objective Optimization Multi Objective Convergent Algorithm Biased Gradient

October 22, 2022

Extractive Summarization of Legal Decisions using Multi-task Learning and Maximal Marginal Relevance
Abhishek Agarwal, Shanshan Xu, Matthias Grabmair
Multi Task Learning Text Summarization Rhetorical Role Summarization Ability Case Summarization Maximal Marginal Relevance

October 18, 2022

Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
Nikolaos Dimitriadis, Pascal Frossard, François Fleuret
Multi Task Learning Diverse Ensemble Pareto Front Single Task Multi Task Benchmark Multiple Task Pareto Manifold

Multi Task Learning

Papers

Mitigating Negative Transfer in Multi-Task Learning with Exponential Moving Average Loss Weighting Strategies

PartAL: Efficient Partial Active Learning in Multi-Task Visual Settings

Enhancing Crisis-Related Tweet Classification with Entity-Masked Language Modeling and Multi-Task Learning

UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning

A Transformer Framework for Data Fusion and Multi-Task Learning in Smart Cities

Multi-task Learning for Sparse Traffic Forecasting

MT4SSL: Boosting Self-Supervised Speech Representation Learning by Integrating Multiple Targets

Enhancing and Adversarial: Improve ASR with Speaker Labels

Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators

Preserving background sound in noise-robust voice conversion via multi-task learning

Multi-task Learning for Source Attribution and Field Reconstruction for Methane Monitoring

Effective Cross-Task Transfer Learning for Explainable Natural Language Inference with T5

Multi-task Bias-Variance Trade-off Through Functional Constraints

Automatic Severity Classification of Dysarthric speech by using Self-supervised Model with Multi-task Learning

Is Multi-Task Learning an Upper Bound for Continual Learning?

M$^3$ViT: Mixture-of-Experts Vision Transformer for Efficient Multi-task Learning with Model-Accelerator Co-design

Analyzing Multi-Task Learning for Abstractive Text Summarization

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach

Extractive Summarization of Legal Decisions using Multi-task Learning and Maximal Marginal Relevance

Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models