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

1,181 papers, page 17 of 24

801. ICML 2024MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance
802. ICML 2024Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
803. ICML 2024Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
804. ICML 2024Multi-group Learning for Hierarchical Groups
805. ICML 2024Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
806. ICML 2024Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning
807. ICML 2024Multi-Source Conformal Inference Under Distribution Shift
808. ICML 2024Multi-View Clustering by Inter-cluster Connectivity Guided Reward
809. ICML 2024Multi-View Stochastic Block Models
810. ICML 2024MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
811. ICML 2024Neural Collapse in Multi-label Learning with Pick-all-label Loss
812. ICML 2024Nonparametric Teaching of Implicit Neural Representations
813. ICML 2024On Multi-Armed Bandit with Impatient Arms
814. ICML 2024On the Emergence of Cross-Task Linearity in Pretraining-Finetuning Paradigm
815. ICML 2024On the Origins of Linear Representations in Large Language Models
816. ICML 2024One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment
817. ICML 2024Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
818. ICML 2024Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
819. ICML 2024Rapid Learning without Catastrophic Forgetting in the Morris Water Maze
820. ICML 2024Regression with Multi-Expert Deferral
821. ICML 2024Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation
822. ICML 2024Representation Surgery for Multi-Task Model Merging
823. ICML 2024Robust Multi-Task Learning with Excess Risks
824. ICML 2024SleepFM: Multi-modal Representation Learning for Sleep Across Brain Activity, ECG and Respiratory Signals
825. ICML 2024Sparse-to-dense Multimodal Image Registration via Multi-Task Learning
826. ICML 2024StrWAEs to Invariant Representations
827. ICML 2024Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments
828. ICML 2024Task Groupings Regularization: Data-Free Meta-Learning with Heterogeneous Pre-trained Models
829. ICML 2024Task-aware Orthogonal Sparse Network for Exploring Shared Knowledge in Continual Learning
830. ICML 2024TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge
831. ICML 2024Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
832. ICML 2024Unbiased Multi-Label Learning from Crowdsourced Annotations
833. NeurIPS 2024$C^2M^3$: Cycle-Consistent Multi-Model Merging
834. NeurIPS 2024$SE(3)$ Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation
835. NeurIPS 2024A New Neural Kernel Regime: The Inductive Bias of Multi-Task Learning
836. NeurIPS 2024A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
837. NeurIPS 2024Adversarially Robust Multi-task Representation Learning
838. NeurIPS 2024AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers
839. NeurIPS 2024Autonomous Agents for Collaborative Task under Information Asymmetry
840. NeurIPS 2024BAKU: An Efficient Transformer for Multi-Task Policy Learning
841. NeurIPS 2024Beyond task diversity: provable representation transfer for sequential multitask linear bandits
842. NeurIPS 2024CoMix: A Comprehensive Benchmark for Multi-Task Comic Understanding
843. NeurIPS 2024CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions
844. NeurIPS 2024Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning
845. NeurIPS 2024DeTeCtive: Detecting AI-generated Text via Multi-Level Contrastive Learning
846. NeurIPS 2024Efficiency for Free: Ideal Data Are Transportable Representations
847. NeurIPS 2024Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters
848. NeurIPS 2024Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance
849. NeurIPS 2024EMR-Merging: Tuning-Free High-Performance Model Merging
850. NeurIPS 2024Evaluate then Cooperate: Shapley-based View Cooperation Enhancement for Multi-view Clustering

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.