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

248 papers, page 5 of 5

201. ICML 2023Bootstrapped Representations in Reinforcement Learning
202. ICML 2023Cluster-Specific Predictions with Multi-Task Gaussian Processes
203. ICML 2023Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects
204. ICML 2023Competing for Shareable Arms in Multi-Player Multi-Armed Bandits
205. ICML 2023Constrained Decision Transformer for Offline Safe Reinforcement Learning
206. ICML 2023Continual Task Allocation in Meta-Policy Network via Sparse Prompting
207. ICML 2023Disentangled Multi-Fidelity Deep Bayesian Active Learning
208. ICML 2023Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
209. ICML 2023Estimating Causal Effects using a Multi-task Deep Ensemble
210. ICML 2023Everyone's Preference Changes Differently: A Weighted Multi-Interest Model For Retrieval
211. ICML 2023FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks
212. ICML 2023Improved Active Multi-Task Representation Learning via Lasso
213. ICML 2023Information-Theoretic State Space Model for Multi-View Reinforcement Learning
214. ICML 2023K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs
215. ICML 2023Learning Intuitive Policies Using Action Features
216. ICML 2023Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation
217. ICML 2023Learning Representations without Compositional Assumptions
218. ICML 2023Less is More: Task-aware Layer-wise Distillation for Language Model Compression
219. ICML 2023MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior
220. ICML 2023Modality-Agnostic Variational Compression of Implicit Neural Representations
221. ICML 2023Multi-Layer Neural Networks as Trainable Ladders of Hilbert Spaces
222. ICML 2023Multi-Objective GFlowNets
223. ICML 2023Multi-Task Differential Privacy Under Distribution Skew
224. ICML 2023Multi-task Hierarchical Adversarial Inverse Reinforcement Learning
225. ICML 2023Multi-Task Off-Policy Learning from Bandit Feedback
226. ICML 2023Multi-task Representation Learning for Pure Exploration in Linear Bandits
227. ICML 2023Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal
228. ICML 2023Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks
229. ICML 2023On Uni-Modal Feature Learning in Supervised Multi-Modal Learning
230. ICML 2023PAC Generalization via Invariant Representations
231. ICML 2023Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
232. ICML 2023Pareto Regret Analyses in Multi-objective Multi-armed Bandit
233. ICML 2023Partially Observable Multi-agent RL with (Quasi-)Efficiency: The Blessing of Information Sharing
234. ICML 2023PCA-based Multi-Task Learning: a Random Matrix Approach
235. ICML 2023Provable Multi-instance Deep AUC Maximization with Stochastic Pooling
236. ICML 2023Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup
237. ICML 2023Recasting Self-Attention with Holographic Reduced Representations
238. ICML 2023Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing
239. ICML 2023Revisiting Pseudo-Label for Single-Positive Multi-Label Learning
240. ICML 2023Robust Subtask Learning for Compositional Generalization
241. ICML 2023Statistical Inference on Multi-armed Bandits with Delayed Feedback
242. ICML 2023Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning
243. ICML 2023Task-Specific Skill Localization in Fine-tuned Language Models
244. ICML 2023Tensor Gaussian Process with Contraction for Multi-Channel Imaging Analysis
245. ICML 2023Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits
246. ICML 2023Towards Understanding Generalization of Macro-AUC in Multi-label Learning
247. ICML 2023Understanding the Complexity Gains of Single-Task RL with a Curriculum
248. ICML 2023Unifying Molecular and Textual Representations via Multi-task Language Modelling

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.