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 22 of 24

1051. ICML 2023On Uni-Modal Feature Learning in Supervised Multi-Modal Learning
1052. ICML 2023PAC Generalization via Invariant Representations
1053. ICML 2023Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
1054. ICML 2023Pareto Regret Analyses in Multi-objective Multi-armed Bandit
1055. ICML 2023Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing
1056. ICML 2023PCA-based Multi-Task Learning: a Random Matrix Approach
1057. ICML 2023Provable Multi-instance Deep AUC Maximization with Stochastic Pooling
1058. ICML 2023Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup
1059. ICML 2023Recasting Self-Attention with Holographic Reduced Representations
1060. ICML 2023Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing
1061. ICML 2023Revisiting Pseudo-Label for Single-Positive Multi-Label Learning
1062. ICML 2023Robust Subtask Learning for Compositional Generalization
1063. ICML 2023Statistical Inference on Multi-armed Bandits with Delayed Feedback
1064. ICML 2023Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning
1065. ICML 2023Task-Specific Skill Localization in Fine-tuned Language Models
1066. ICML 2023Tensor Gaussian Process with Contraction for Multi-Channel Imaging Analysis
1067. ICML 2023Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits
1068. ICML 2023Towards Understanding Generalization of Macro-AUC in Multi-label Learning
1069. ICML 2023Understanding the Complexity Gains of Single-Task RL with a Curriculum
1070. ICML 2023Unifying Molecular and Textual Representations via Multi-task Language Modelling
1071. NeurIPS 2023A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
1072. NeurIPS 2023AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks
1073. NeurIPS 2023Achieving Cross Modal Generalization with Multimodal Unified Representation
1074. NeurIPS 2023Active Bipartite Ranking
1075. NeurIPS 2023Active representation learning for general task space with applications in robotics
1076. NeurIPS 2023Addressing Negative Transfer in Diffusion Models
1077. NeurIPS 2023Agnostic Multi-Group Active Learning
1078. NeurIPS 2023AIMS: All-Inclusive Multi-Level Segmentation for Anything
1079. NeurIPS 2023An active learning framework for multi-group mean estimation
1080. NeurIPS 2023Analysis of Variance of Multiple Causal Networks
1081. NeurIPS 2023Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
1082. NeurIPS 2023Bandit Social Learning under Myopic Behavior
1083. NeurIPS 2023Bandit Task Assignment with Unknown Processing Time
1084. NeurIPS 2023BanditPAM++: Faster $k$-medoids Clustering
1085. NeurIPS 2023CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes
1086. NeurIPS 2023Cappy: Outperforming and Boosting Large Multi-Task LMs with a Small Scorer
1087. NeurIPS 2023Chatting Makes Perfect: Chat-based Image Retrieval
1088. NeurIPS 2023Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
1089. NeurIPS 2023CMMA: Benchmarking Multi-Affection Detection in Chinese Multi-Modal Conversations
1090. NeurIPS 2023Connecting Multi-modal Contrastive Representations
1091. NeurIPS 2023Conservative Offline Policy Adaptation in Multi-Agent Games
1092. NeurIPS 2023Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning
1093. NeurIPS 2023Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
1094. NeurIPS 2023DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model
1095. NeurIPS 2023Decompose a Task into Generalizable Subtasks in Multi-Agent Reinforcement Learning
1096. NeurIPS 2023Deep Momentum Multi-Marginal Schrödinger Bridge
1097. NeurIPS 2023Demystifying the Optimal Performance of Multi-Class Classification
1098. NeurIPS 2023DIFFER:Decomposing Individual Reward for Fair Experience Replay in Multi-Agent Reinforcement Learning
1099. NeurIPS 2023Diffused Task-Agnostic Milestone Planner
1100. NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms

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.