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

171 papers, page 4 of 4

151. ICLR 2023Multi-level Protein Structure Pre-training via Prompt Learning
152. ICLR 2023Multi-objective optimization via equivariant deep hypervolume approximation
153. ICLR 2023Multi-Rate VAE: Train Once, Get the Full Rate-Distortion Curve
154. ICLR 2023Multi-skill Mobile Manipulation for Object Rearrangement
155. ICLR 2023Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization
156. ICLR 2023Multimodal Federated Learning via Contrastive Representation Ensemble
157. ICLR 2023Not All Tasks Are Born Equal: Understanding Zero-Shot Generalization
158. ICLR 2023Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes
159. ICLR 2023Q-Pensieve: Boosting Sample Efficiency of Multi-Objective RL Through Memory Sharing of Q-Snapshots
160. ICLR 2023Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning
161. ICLR 2023Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting
162. ICLR 2023Simple Emergent Action Representations from Multi-Task Policy Training
163. ICLR 2023SLTUNET: A Simple Unified Model for Sign Language Translation
164. ICLR 2023SMART: Self-supervised Multi-task pretrAining with contRol Transformers
165. ICLR 2023Stochastic Multi-Person 3D Motion Forecasting
166. ICLR 2023STREET: A MULTI-TASK STRUCTURED REASONING AND EXPLANATION BENCHMARK
167. ICLR 2023Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
168. ICLR 2023Task-customized Masked Autoencoder via Mixture of Cluster-conditional Experts
169. ICLR 2023TaskPrompter: Spatial-Channel Multi-Task Prompting for Dense Scene Understanding
170. ICLR 2023Using Both Demonstrations and Language Instructions to Efficiently Learn Robotic Tasks
171. ICLR 2023Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding

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.