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

111 papers, page 1 of 3

1. NeurIPS 2023A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
2. NeurIPS 2023AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks
3. NeurIPS 2023Achieving Cross Modal Generalization with Multimodal Unified Representation
4. NeurIPS 2023Active Bipartite Ranking
5. NeurIPS 2023Active representation learning for general task space with applications in robotics
6. NeurIPS 2023Addressing Negative Transfer in Diffusion Models
7. NeurIPS 2023Agnostic Multi-Group Active Learning
8. NeurIPS 2023AIMS: All-Inclusive Multi-Level Segmentation for Anything
9. NeurIPS 2023An active learning framework for multi-group mean estimation
10. NeurIPS 2023Analysis of Variance of Multiple Causal Networks
11. NeurIPS 2023Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
12. NeurIPS 2023Bandit Social Learning under Myopic Behavior
13. NeurIPS 2023Bandit Task Assignment with Unknown Processing Time
14. NeurIPS 2023BanditPAM++: Faster $k$-medoids Clustering
15. NeurIPS 2023CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes
16. NeurIPS 2023Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
17. NeurIPS 2023Chatting Makes Perfect: Chat-based Image Retrieval
18. NeurIPS 2023Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
19. NeurIPS 2023CMMA: Benchmarking Multi-Affection Detection in Chinese Multi-Modal Conversations
20. NeurIPS 2023Connecting Multi-modal Contrastive Representations
21. NeurIPS 2023Conservative Offline Policy Adaptation in Multi-Agent Games
22. NeurIPS 2023Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning
23. NeurIPS 2023Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
24. NeurIPS 2023DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
25. NeurIPS 2023Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning
26. NeurIPS 2023Deep Momentum Multi-Marginal Schrödinger Bridge
27. NeurIPS 2023Demystifying the Optimal Performance of Multi-Class Classification
28. NeurIPS 2023DIFFER:Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
29. NeurIPS 2023Diffused Task-Agnostic Milestone Planner
30. NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
31. NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
32. NeurIPS 2023Elastic Decision Transformer
33. NeurIPS 2023Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback
34. NeurIPS 2023Episodic Multi-Task Learning with Heterogeneous Neural Processes
35. NeurIPS 2023Factorized Contrastive Learning: Going Beyond Multi-view Redundancy
36. NeurIPS 2023Federated Multi-Objective Learning
37. NeurIPS 2023FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery
38. NeurIPS 2023ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning
39. NeurIPS 2023Generalized test utilities for long-tail performance in extreme multi-label classification
40. NeurIPS 2023Geodesic Multi-Modal Mixup for Robust Fine-Tuning
41. NeurIPS 2023Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning
42. NeurIPS 2023Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection
43. NeurIPS 2023HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork
44. NeurIPS 2023ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns
45. NeurIPS 2023Joint Data-Task Generation for Auxiliary Learning
46. NeurIPS 2023Learning and Collusion in Multi-unit Auctions
47. NeurIPS 2023Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning
48. NeurIPS 2023Learning Human Action Recognition Representations Without Real Humans
49. NeurIPS 2023Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head
50. NeurIPS 2023Learning Shared Safety Constraints from Multi-task Demonstrations

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.