Multi-Task Learning papers, 2023–2026

Key findings

• Multi-Task Learning went from 288 papers in 2023 to 402 in 2026, roughly 1.4x in three years.
• NeurIPS publishes the most Multi-Task Learning work: 399 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with Datasets and Benchmarks: papers tagged with both rose from 6 in 2023 to 16 in 2026.
• Among the 5 topics under Meta-Learning and Transfer, it ranks #2 by 2026 paper count; the fastest grower in the group, Foundation Model Adaptation, is up 3.8x versus 1.4x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Mahalanobis Margin \texorpdfstring{$\gamma_{\min}$}{gamma\_min} Bound on Task Confusion in Pretrained Class-Incremental Learning: From Infeasibility to Exponential Attenuation
• ICML 2026A Systematic Study of Behavioral Cloning for Scientific Data Annotation
• ICLR 2026Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?
• CVPR 20263D-Aware Multi-Task Learning with Cross-View Correlations for Dense Scene Understanding
• NeurIPS 2025A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
• ICML 2025ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
• ICLR 2025CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
• CVPR 2025ACAttack: Adaptive Cross Attacking RGB-T Tracker via Multi-Modal Response Decoupling
• NeurIPS 2024CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
• ICML 2024Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
• ICLR 2024Class Incremental Learning via Likelihood Ratio Based Task Prediction
• CVPR 2024Differentiable Information Bottleneck for Deterministic Multi-view Clustering
• NeurIPS 2023A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
• ICML 2023A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging
• ICLR 2023An Extensible Multi-modal Multi-task Object Dataset with Materials
• CVPR 2023AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation
• NeurIPS 2026A Scalable Multi-Task Model for Virtual Sensors
• ICML 2026Alleviating Observation Bias via Causal-Invariant Meta-Learning for Unbalanced Incomplete Multi-view Clustering
• ICLR 2026Beyond Hearing: Learning Task-agnostic ExG Representations from Earphones via Physiology-informed Tokenization
• CVPR 2026Any Resolution Any Geometry From Multi-View To Multi-Patch

All Multi-Task Learning papers

31 papers, page 1 of 1

1. ICLR 2024AdaMerging: Adaptive Model Merging for Multi-Task Learning
2. ICLR 2024Augmenting Transformers with Recursively Composed Multi-grained Representations
3. ICLR 2024Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
4. ICLR 2024Class Incremental Learning via Likelihood Ratio Based Task Prediction
5. ICLR 2024CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding
6. ICLR 2024Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback
7. ICLR 2024Controlling Vision-Language Models for Multi-Task Image Restoration
8. ICLR 2024Customizable Combination of Parameter-Efficient Modules for Multi-Task Learning
9. ICLR 2024Denoising Task Routing for Diffusion Models
10. ICLR 2024Diffusion Models for Multi-Task Generative Modeling
11. ICLR 2024Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
12. ICLR 2024DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
13. ICLR 2024Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
14. ICLR 2024From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction
15. ICLR 2024GenSim: Generating Robotic Simulation Tasks via Large Language Models
16. ICLR 2024Hybrid Sharing for Multi-Label Image Classification
17. ICLR 2024MAP IT to Visualize Representations
18. ICLR 2024MUFFIN: Curating Multi-Faceted Instructions for Improving Instruction Following
19. ICLR 2024Multi-Scale Representations by Varying Window Attention for Semantic Segmentation
20. ICLR 2024Multi-task Learning with 3D-Aware Regularization
21. ICLR 2024Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts
22. ICLR 2024Multi-View Causal Representation Learning with Partial Observability
23. ICLR 2024Multi-View Representation is What You Need for Point-Cloud Pre-Training
24. ICLR 2024MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
25. ICLR 2024Object-Centric Learning with Slot Mixture Module
26. ICLR 2024Octavius: Mitigating Task Interference in MLLMs via LoRA-MoE
27. ICLR 2024Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
28. ICLR 2024Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes
29. ICLR 2024Robot Fleet Learning via Policy Merging
30. ICLR 2024Task structure and nonlinearity jointly determine learned representational geometry
31. ICLR 2024Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets

FAQ

How many Multi-Task Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,181 in total: 288 in 2023, 227 in 2024, 264 in 2025, 402 in 2026.

How many Multi-Task Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 126 Multi-Task Learning papers, versus 101 the year before.

How many Multi-Task Learning papers are at ICLR 2026?

ICLR 2026 has 57 Multi-Task Learning papers, versus 40 the year before.

How many Multi-Task Learning papers are at ICML 2026?

ICML 2026 has 91 Multi-Task Learning papers, versus 47 the year before.

How many Multi-Task Learning papers are at CVPR 2026?

CVPR 2026 has 128 Multi-Task Learning papers, versus 76 the year before.

Which conference publishes the most Multi-Task Learning papers?

NeurIPS, with 399 papers from 2023 to 2026.