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

40 papers, page 1 of 1

1. ICLR 2025Active Task Disambiguation with LLMs
2. ICLR 2025Balanced Ranking with Relative Centrality: A multi-core periphery perspective
3. ICLR 2025CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
4. ICLR 2025CREIMBO: Cross-Regional Ensemble Interactions in Multi-view Brain Observations
5. ICLR 2025Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
6. ICLR 2025Denoising Task Difficulty-based Curriculum for Training Diffusion Models
7. ICLR 2025DEPT: Decoupled Embeddings for Pre-training Language Models
8. ICLR 2025Disentangling Representations through Multi-task Learning
9. ICLR 2025Dynamic Modeling of Patients, Modalities and Tasks via Multi-modal Multi-task Mixture of Experts
10. ICLR 2025Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training
11. ICLR 2025Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic
12. ICLR 2025GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
13. ICLR 2025Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
14. ICLR 2025Learning Diagrams: A Graphical Language for Compositional Training Regimes
15. ICLR 2025Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning
16. ICLR 2025Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
17. ICLR 2025LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging
18. ICLR 2025Many-Objective Multi-Solution Transport
19. ICLR 2025MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
20. ICLR 2025Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement
21. ICLR 2025Mitigating Parameter Interference in Model Merging via Sharpness-Aware Fine-Tuning
22. ICLR 2025Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace
23. ICLR 2025MTSAM: Multi-Task Fine-Tuning for Segment Anything Model
24. ICLR 2025Multi-objective Differentiable Neural Architecture Search
25. ICLR 2025Multi-Resolution Decomposable Diffusion Model for Non-Stationary Time Series Anomaly Detection
26. ICLR 2025Multi-session, multi-task neural decoding from distinct cell-types and brain regions
27. ICLR 2025Multi-Task Dense Predictions via Unleashing the Power of Diffusion
28. ICLR 2025NeuroLM: A Universal Multi-task Foundation Model for Bridging the Gap between Language and EEG Signals
29. ICLR 2025Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences
30. ICLR 2025Perm: A Parametric Representation for Multi-Style 3D Hair Modeling
31. ICLR 2025Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
32. ICLR 2025REVISITING MULTI-PERMUTATION EQUIVARIANCE THROUGH THE LENS OF IRREDUCIBLE REPRESENTATIONS
33. ICLR 2025Selective Task Group Updates for Multi-Task Optimization
34. ICLR 2025SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels
35. ICLR 2025STAFF: Speculative Coreset Selection for Task-Specific Fine-tuning
36. ICLR 2025Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
37. ICLR 2025Task Descriptors Help Transformers Learn Linear Models In-Context
38. ICLR 2025Towards Optimal Multi-draft Speculative Decoding
39. ICLR 2025When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers
40. ICLR 2025Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression

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.