Multi-Task Optimization

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Overview

Multi-task optimization studies how to improve several related tasks or objectives together, from training one model across datasets to searching for solutions across related optimization problems. Common approaches share representations or task information, balance losses, and use gradient surgery to reduce interference; multi-objective methods also use scalarization and Pareto-front search to expose trade-offs. Bayesian and evolutionary methods transfer information between tasks, sometimes using task graphs or learned task relationships. A central tension is that sharing can save data and computation but cause negative transfer when tasks differ, while conflicting objectives and mismatched loss scales make reliable balancing difficult.

Latest papers

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49 papers7 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. Near-optimal and Efficient First-Order Algorithm for Multi-Task Learning with Shared Linear Representation

    May 1, 2026Shihong Ding, Fangyu Du, Cong FangShared Representation LearningRepresentation Learning

    State Key Lab of General AI, School of Intelligence Science and Technology, Peking University, China · School of Mathematical Sciences, Peking University, China · Institute for Artificial Intelligence, Peking University, China

  2. Multi-Task Optimization over Networks of Tasks

    Apr 23, 2026Julian Hatzky, Thomas Bartz-Beielstein, A. E. Eiben +1Evolutionary OptimizationEvolutionary Multitask Optimization

    Vrije Universiteit Amsterdam, Amsterdam, The Netherlands · TH Köln, Cologne, Germany

  3. Analysis of Multitasking Pareto Optimization for Monotone Submodular Problems

    Apr 16, 2026Liam Wigney, Frank NeumannSubmodular OptimizationEvolutionary Optimization

    Optimisation and Logistics School of Computer Science and Information Technology Adelaide University Adelaide, Australia

  4. BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH

    Apr 13, 2026Rahman Ejaz, Varchas Gopalaswamy, Ricardo Luna +5Bayesian OptimizationMulti-Task Optimization

    Laboratory for Laser Energetics, Rochester, NY, USA · Department of Mechanical Engineering, University of Rochester, Rochester, NY, USA · Hewlett Packard Labs, Santa Clara, CA, USA +2

  5. Delve into the Applicability of Advanced Optimizers for Multi-Task Learning

    Apr 10, 2026Zhipeng Zhou, Linxiao Cao, Pengcheng Wu +2Orthogonal OptimizationMulti-Task Learning

    Nanyang Technological University · Hong Kong University of Science and Technology (Guangzhou) · School of Artificial Intelligence, Shanghai Jiao Tong University

  6. Task-Guided Multi-Annotation Triplet Learning for Remote Sensing Representations

    Apr 4, 2026Meilun Zhou, Alina ZareRepresentation LearningMulti-Task Learning

    Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA, 32611 · Artificial Intelligence and Informatics Research Institute, University of Florida, Gainesville, FL, USA, 32611

  7. TransGP: Task-Conditioned Transformer-Guided Genetic Programming for Multitask Dynamic Flexible Job Shop Scheduling

    Apr 4, 2026Meng Xu, Jiao Liu, Hua Yu +1Job Shop SchedulingAutomated Heuristic Design

  8. Finding Sets of Pareto Sets in Real-World Scenarios -- A Multitask Multiobjective Perspective

    Apr 4, 2026Jiao Liu, Yew Soon Ong, Melvin WongEvolutionary Multitask OptimizationMulti-Objective Optimization

    College of Computing & Data Science, Nanyang Technological University, Singapore

  9. Double Coupling Architecture and Training Method for Optimization Problems of Differential Algebraic Equations with Parameters

    Mar 24, 2026Wenqiang Yang, Wenyuan Wu, Yong Feng +1Constrained OptimizationPhysics-Informed ML

    Chongqing Key Laboratory of Automated Reasoning and Cognition, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, 266 Fangzheng Avenue, Liangjiang District, 400714, Chongqing, China. · Chongqing School, University of Chinese Academy of Sciences, 266 Fangzheng Avenue, Liangjiang District, 400714, Chongqing, China.

  10. mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT

    Mar 23, 2026Woosung Koh, Jeyoung Jeon, Youngjin Song +4LLM Fine-TuningSupervised Fine-Tuning

    KAIST AI · Yonsei University · Samsung Advanced Institute of Technology

  11. UniPINN: A Unified PINN Framework for Multi-task Learning of Diverse Navier-Stokes Equations

    Mar 11, 2026Dengdi Sun, Jie Chen, Xiao Wang +1Physics-Informed MLMulti-Task Learning

    Key Laboratory of Intelligent Computing & Signal Processing (ICSP), Ministry of Education, School of Artificial Intelligence, Anhui University, Hefei 230601, China · Anhui Provincial Key Laboratory of Multimodal Cognitive Computing, School of Computer Science and Technology, Anhui University, Hefei 230601, China

  12. Asymptotic Behavior of Multi--Task Learning: Implicit Regularization and Double Descent Effects

    Mar 5, 2026Ayed M. Alrashdi, Oussama Dhifallah, Houssem SifaouDouble DescentNeural Network Generalization

    Department of Electrical Engineering, College of Engineering, University of Ha’il, P.O. Box 2440, Ha’il, 81441, Saudi Arabia · John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA · Department of Electrical and Electronic Engineering, King’s College London – Strand, London WC2R 2LS – London, UK

  13. Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?

    Mar 2, 2026Semih Cantürk, Thomas Sabourin, Frederik Wenkel +2Neural Combinatorial OptimizationTransfer Learning

    Dept. of Computer Science and Operations Research, Université de Montréal · Mila – Quebec AI Institute · Dept. of Mathematics & Statistics, Université de Montréal +2

  14. DeepMTL2R: A Library for Deep Multi-task Learning to Rank

    Feb 16, 2026Chaosheng Dong, Peiyao Xiao, Yijia Wang +1Learning to RankMulti-Task Learning

    Amazon USA

  15. Multi-Task Learning for Metal Alloy Property Prediction: An Empirical Study of Negative Transfer and Mitigation Strategies

    Dec 28, 2025Sungwoo KangMulti-Task LearningMaterials Property Prediction

    Department of Electrical and Computer Engineering, Korea University, Seoul 02841, Republic of Korea

  16. Graph Coloring for Multi-Task Learning

    Sep 21, 2025Santosh Patapati, Ian NoronhaGradient InterferenceMulti-Task Learning

    Stony Brook University AI Innovation Institute, Stony Brook, NY 11794, USA · Purdue University, West Lafayette, IN 47907, USA

  17. Learning Task Mixtures from Task Affinities: A Probabilistic Graphical Model for Supervised Fine-Tuning

    Jul 16, 2025Prateek Chanda, Saral Sureka, Parth Pratim Chatterjee +3Supervised Fine-TuningMulti-Task Learning

    IIT Bombay · IBM Research · Red Hat AI Innovation +1

  18. (θl,θuθ_l, θ_u)-Parametric Multi-Task Optimization: Joint Search in Solution and Infinite Task Spaces

    Mar 11, 2025Tingyang Wei, Jiao Liu, Abhishek Gupta +2Evolutionary OptimizationMulti-Task Optimization

    College of Computing and Data Science, Nanyang Technological University, Singapore · School of Mechanical Sciences, Indian Institute of Technology, Goa, India · Singapore Institute of Manufacturing Technology (SIMTech), Agency for Science, Technology and Research, Singapore +1

  19. Variational Model Merging for Pareto Front Estimation in Multitask Finetuning

    Dec 11, 2024Hugo Monzón Maldonado, Nico Daheim, Thomas Möllenhoff +2Bayesian InferenceMulti-Task Learning

    RIKEN Center for AI Project, Japan · Ubiquitous Knowledge Processing Lab (UKP Lab), Department of Computer Science, Technical University of Darmstadt and National Research Center for Applied Cybersecurity ATHENE, Germany · National Research Center for Applied Cybersecurity ATHENE, Germany