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

126 papers, page 1 of 3

1. NeurIPS 2026A Black-Box Reduction from Regret to Multi-Level Coverage
2. NeurIPS 2026A Mahalanobis Margin \texorpdfstring{$\gamma_{\min}$}{gamma\_min} Bound on Task Confusion in Pretrained Class-Incremental Learning: From Infeasibility to Exponential Attenuation
3. NeurIPS 2026A Scalable Multi-Task Model for Virtual Sensors
4. NeurIPS 2026A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning
5. NeurIPS 2026Adaptive LLM Routing for Multi-Turn Conversations with Continuously Evolving User Queries
6. NeurIPS 2026Adaptive Multi-view Graph Contrastive Learning via Fractional Continuous Dynamics
7. NeurIPS 2026AgentRoom: Concurrent Multi-Agent Coding in a CRDT-Backed Shared Workspace
8. NeurIPS 2026ArcMark: Distortion-Free Multi-Byte LLM Watermark via Optimal Transport
9. NeurIPS 2026ASTOR: Multi-Task Code Reinforcement Learning via Utility-Driven Coordination
10. NeurIPS 2026Attention Is More Than You Need: Spectral Redundancy in Multi-Head Routing
11. NeurIPS 2026BACE: Behavior-Adaptive Connectivity Estimation from Multi-Region Neural Recordings
12. NeurIPS 2026Balanced Multi-Task Learning from an Optimality-Gap Perspective
13. NeurIPS 2026Bandits via Additive Quantized Representations
14. NeurIPS 2026Benchmarking Open-Ended Multi-Agent Coordination in Language Agents
15. NeurIPS 2026BESS-Bench: Benchmarking Spectral Representations for Be-Star Variability
16. NeurIPS 2026Beyond FLOPs: Train-Full, Deploy-Partial Multi-Exit Inference via Selective Lightweight IC Ensemble
17. NeurIPS 2026Beyond Outcome: Trajectory-Driven Prompt Optimization via Multi-Dimensional Rewards
18. NeurIPS 2026Beyond Semantic Alignment: Geometric Incomparability in Multi-Oracle Soft Fusion
19. NeurIPS 2026Bilevel Optimization of Synthetic Trajectories for Multi-Turn LLM Fine-Tuning
20. NeurIPS 2026BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
21. NeurIPS 2026BrainCoT: A Multi-Task Zero-Shot Brain Signal Foundation Model with Neurometric-Anchored Chain-of-Thought Reasoning
22. NeurIPS 2026C3P: Contrastive promoter-protein pretraining yields representations capturing bacterial gene regulation
23. NeurIPS 2026Can Metadata Fix the Gauge? Calibration Turns Sparse Multi-Source Learning from Sparse PCA into Sparse Mean Recovery
24. NeurIPS 2026Causal Multi-Task Demand Learning
25. NeurIPS 2026CoDeRNet: Selective Cross-Task Routing under Heterogeneous Supervision for Change Detection and Captioning
26. NeurIPS 2026Compressible Representations: Functional Spines in Deep Neural Networks
27. NeurIPS 2026Constructive Neural Policies for the Quadratic Assignment Problem via Multi-Expert Imitation
28. NeurIPS 2026Cross-Family Universality of Behavioral Axes via Anchor-Projected Representations
29. NeurIPS 2026Cross-User Poisoning: User-Task Boundary Failures in Multi-User Collaborative Language Agents
30. NeurIPS 2026Crowded in B-Space: Calibrating Shared Directions for LoRA Merging
31. NeurIPS 2026Curvature-Guided Parameter Initialization for Multi-Task Learning
32. NeurIPS 2026Cyclic Discrete Diffusion: A Novel Multi-Class Segmentation Refinement Technique
33. NeurIPS 2026DC-ViT: Modulating Spatial and Channel Interactions for Multi-Channel Images
34. NeurIPS 2026DDMS: Discriminative Distillation of Multi-view Foundational Features into Single-view Models
35. NeurIPS 2026Decomposed Representations Mitigate the Alignment–Specificity Trade-off in Multi-Omics
36. NeurIPS 2026Deconstructing Multi-Task Active Learning: The Paradox of Gradient Conflict and Orthogonal Decomposition
37. NeurIPS 2026Delve into the Applicability of Advanced Optimizers for Multi-Task Learning
38. NeurIPS 2026Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning
39. NeurIPS 2026Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
40. NeurIPS 2026Driver Attention as Competitive Allocation: A Scene--Task-Aware Dual-Branch Framework
41. NeurIPS 2026EEG Benchmarking Needs a Task Specification Layer: NeuroDoc for Rulebook-Guided, Executable Benchmark Construction
42. NeurIPS 2026Efficient SAM 3 Adaptation for Multi-Class Semantic Segmentation via Dense Competitive Representations
43. NeurIPS 2026Elastic Representations via Hyperbolic Geometry
44. NeurIPS 2026Exponential Map Models as an Interpretable Framework for Generating Neural Spatial Representations
45. NeurIPS 2026Focusable Monocular Depth Estimation
46. NeurIPS 2026From Isolated feature to Orbits:\\Discovering Music Concepts via Multi-SAE Alignment
47. NeurIPS 2026Frontier Task Synthesis Via Solution-Centric Evolution
48. NeurIPS 2026Grouped Adaptive Head Mixing for Personalized Multi-Task Federated Reinforcement Learning
49. NeurIPS 2026Harder the Task, Sparser the Representation: Sparsity as a Learning Signature of Capability in LLMs
50. NeurIPS 2026How are linear representations learned? Exact solutions to the dynamics of abstraction

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.