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

43 papers, page 1 of 1

1. ICLR 2023An Additive Instance-Wise Approach to Multi-class Model Interpretation
2. ICLR 2023An Extensible Multi-modal Multi-task Object Dataset with Materials
3. ICLR 2023BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection
4. ICLR 2023Clean-image Backdoor: Attacking Multi-label Models with Poisoned Labels Only
5. ICLR 2023Composite Slice Transformer: An Efficient Transformer with Composition of Multi-Scale Multi-Range Attentions
6. ICLR 2023Compositional Task Representations for Large Language Models
7. ICLR 2023Deep Learning on Implicit Neural Representations of Shapes
8. ICLR 2023Editing models with task arithmetic
9. ICLR 2023Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task
10. ICLR 2023Enhancing Meta Learning via Multi-Objective Soft Improvement Functions
11. ICLR 2023Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning
12. ICLR 2023Evaluating Representations with Readout Model Switching
13. ICLR 2023Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
14. ICLR 2023f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
15. ICLR 2023HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers
16. ICLR 2023How to prepare your task head for finetuning
17. ICLR 2023HypeR: Multitask Hyper-Prompted Training Enables Large-Scale Retrieval Generalization
18. ICLR 2023Investigating Multi-task Pretraining and Generalization in Reinforcement Learning
19. ICLR 2023Is a Caption Worth a Thousand Images? A Study on Representation Learning
20. ICLR 2023Learning Proximal Operators to Discover Multiple Optima
21. ICLR 2023Learning topology-preserving data representations
22. ICLR 2023Mitigating Memorization of Noisy Labels via Regularization between Representations
23. ICLR 2023Multi-level Protein Structure Pre-training via Prompt Learning
24. ICLR 2023Multi-objective optimization via equivariant deep hypervolume approximation
25. ICLR 2023Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
26. ICLR 2023Multi-skill Mobile Manipulation for Object Rearrangement
27. ICLR 2023Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
28. ICLR 2023Multimodal Federated Learning via Contrastive Representation Ensemble
29. ICLR 2023Not All Tasks Are Born Equal: Understanding Zero-Shot Generalization
30. ICLR 2023Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes
31. ICLR 2023Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots
32. ICLR 2023Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning
33. ICLR 2023Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
34. ICLR 2023Simple Emergent Action Representations from Multi-Task Policy Training
35. ICLR 2023SLTUNET: A Simple Unified Model for Sign Language Translation
36. ICLR 2023SMART: Self-supervised Multi-task pretrAining with contRol Transformers
37. ICLR 2023Stochastic Multi-Person 3D Motion Forecasting
38. ICLR 2023STREET: A MULTI-TASK STRUCTURED REASONING AND EXPLANATION BENCHMARK
39. ICLR 2023Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
40. ICLR 2023Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts
41. ICLR 2023TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding
42. ICLR 2023Using Both Demonstrations and Language Instructions to Efficiently Learn Robotic Tasks
43. ICLR 2023Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding

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.