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

101 papers, page 1 of 3

1. NeurIPS 2025$i$MIND: Insightful Multi-subject Invariant Neural Decoding
2. NeurIPS 2025A Data-Driven Prism: Multi-View Source Separation with Diffusion Model Priors
3. NeurIPS 2025A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
4. NeurIPS 2025A Minimalistic Unified Framework for Incremental Learning across Image Restoration Tasks
5. NeurIPS 2025A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
6. NeurIPS 2025Adaptable Safe Policy Learning from Multi-task Data with Constraint Prioritized Decision Transformer
7. NeurIPS 2025AF-UMC: An Alignment-Free Fusion Framework for Unaligned Multi-View Clustering
8. NeurIPS 2025Are Greedy Task Orderings Better Than Random in Continual Linear Regression?
9. NeurIPS 2025Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners
10. NeurIPS 2025Bit-swapping Oriented Twin-memory Multi-view Clustering in Lifelong Incomplete Scenarios
11. NeurIPS 2025Cameras as Relative Positional Encoding
12. NeurIPS 2025Can Class-Priors Help Single-Positive Multi-Label Learning?
13. NeurIPS 2025Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?
14. NeurIPS 2025Confidence-Aware With Prototype Alignment for Partial Multi-label Learning
15. NeurIPS 2025Connecting Neural Models Latent Geometries with Relative Geodesic Representations
16. NeurIPS 2025Constructing an Optimal Behavior Basis for the Option Keyboard
17. NeurIPS 2025Continual Model Merging without Data: Dual Projections for Balancing Stability and Plasticity
18. NeurIPS 2025Continual Optimization with Symmetry Teleportation for Multi-Task Learning
19. NeurIPS 2025Contribution of task-irrelevant stimuli to drift of neural representations
20. NeurIPS 2025CSI-Bench: A Large-Scale In-the-Wild Dataset for Multi-task WiFi Sensing
21. NeurIPS 2025DeepASA: An Object-Oriented Multi-Purpose Network for Auditory Scene Analysis
22. NeurIPS 2025DICEPTION: A Generalist Diffusion Model for Visual Perceptual Tasks
23. NeurIPS 2025DINO-Foresight: Looking into the Future with DINO
24. NeurIPS 2025Diversity-oriented Deep Multi-modal Clustering
25. NeurIPS 2025Do different prompting methods yield a common task representation in language models?
26. NeurIPS 2025EgoDTM: Towards 3D-Aware Egocentric Video-Language Pretraining
27. NeurIPS 2025Exploiting Task Relationships in Continual Learning via Transferability-Aware Task Embeddings
28. NeurIPS 2025Exploring Tradeoffs through Mode Connectivity for Multi-Task Learning
29. NeurIPS 2025Extracting task-relevant preserved dynamics from contrastive aligned neural recordings
30. NeurIPS 2025Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
31. NeurIPS 2025Federated Continual Learning via Orchestrating Multi-Scale Expertise
32. NeurIPS 2025Federated Multi-armed Bandits with Efficient Bit-Level Communications
33. NeurIPS 2025FedMGP: Personalized Federated Learning with Multi-Group Text-Visual Prompts
34. NeurIPS 2025FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
35. NeurIPS 2025Find your Needle: Small Object Image Retrieval via Multi-Object Attention Optimization
36. NeurIPS 2025GAMMA: Gated Multi-hop Message Passing for Homophily-Agnostic Node Representation in GNNs
37. NeurIPS 2025GRAPE: Optimize Data Mixture for Group Robust Multi-target Adaptive Pretraining
38. NeurIPS 2025GreenHyperSpectra: A multi-source hyperspectral dataset for global vegetation trait prediction
39. NeurIPS 2025Guard Me If You Know Me: Protecting Specific Face-Identity from Deepfakes
40. NeurIPS 2025HM3: Hierarchical Multi-Objective Model Merging for Pretrained Models
41. NeurIPS 2025HyperET: Efficient Training in Hyperbolic Space for Multi-modal Large Language Models
42. NeurIPS 2025Hypergraph-Enhanced Contrastive Learning for Multi-View Clustering with Hyper-Laplacian Regularization
43. NeurIPS 2025IDOL: Meeting Diverse Distribution Shifts with Prior Physics for Tropical Cyclone Multi-Task Estimation
44. NeurIPS 2025Learn and Ensemble Bridge Adapters for Multi-domain Task Incremental Learning
45. NeurIPS 2025Learning from Disjoint Views: A Contrastive Prototype Matching Network for Fully Incomplete Multi-View Clustering
46. NeurIPS 2025Learning Multi-Source and Robust Representations for Continual Learning
47. NeurIPS 2025Learning Orthogonal Multi-Index Models: A Fine-Grained Information Exponent Analysis
48. NeurIPS 2025Learning Shared Representations from Unpaired Data
49. NeurIPS 2025Learning Task-Agnostic Representations through Multi-Teacher Distillation
50. NeurIPS 2025LIFEBENCH: Evaluating Length Instruction Following in Large Language Models

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.