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 5 of 24

201. ICML 2026CrossQ: Task-Aligned Cross-Token Conditional Quantization for Late Interaction Retrieval
202. ICML 2026Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks
203. ICML 2026Decentralized Instruction Tuning: Conflict-Aware Splitting and Weight Merging
204. ICML 2026DecodeShare: Tracing the Shared Subspace of LLM Decode-Time Decisions
205. ICML 2026Decomposing the Basic Abilities of Large Language Models: Mitigating Cross-Task Interference in Multi-Task Instruct-Tuning
206. ICML 2026Discretely-Refined Multi-view Clustering via Aligned Anchor Learning
207. ICML 2026Distilling Linearized Behavior into Non-linear Fine-Tuning for Effective Task Arithmetic
208. ICML 2026Distilling Task-Level Coordination Policies for Generalizable Multi-Agent Cooperation
209. ICML 2026DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs
210. ICML 2026Dual-Calibration Multi-View Clustering via Compact Anchor Learning
211. ICML 2026Efficient Training-Free Multi-Token Prediction via Embedding-Space Probing
212. ICML 2026Evaluating and Steering Modality Preferences in Multi-modal LLMs
213. ICML 2026FACT: Fuzzy Alignment with Comorbidity Topology for Reliable Multi-Label Medical Image Diagnosis
214. ICML 2026Factored Latent Action World Models
215. ICML 2026Feedback Control for Multi-Objective Graph Self-Supervision
216. ICML 2026FiGuRO: Intrinsic Dimension Estimation for Multi-Modal Data
217. ICML 2026Fine-Tune Once, Reuse Across Models: Bayesian Task-Update Factors and Approximations
218. ICML 2026From 2D Grids to 1D Tokens: Reforming Shared Representations for Multimodal Image Fusion
219. ICML 2026GCIB: Graph Contrastive Information Bottleneck for Multi-Behavior Recommendation
220. ICML 2026Geometric Pocket-Centric Protein Encoding for Polypharmacology-Guided Multi-Target Drug Design
221. ICML 2026Goal-Conditioned Agents that Learn Everything All at Once
222. ICML 2026Gradient Descent with Large Step Size Restores Symmetry in Deep Linear Networks with Multi-Pathway
223. ICML 2026HASTE: Hardware-Aware Dynamic Sparse Training for Large Output Spaces
224. ICML 2026Hierarchical Anchor Graph Learning for Multi-View Clustering
225. ICML 2026Hierarchical Representations for Cross-task Automated Heuristic Design using LLMs
226. ICML 2026HyMTRL: A Hybrid Multi-Task Reinforcement Learning Framework via Phased Policy Evolution
227. ICML 2026Hyperparameter Transfer Laws for Non-Recurrent Multi-Path Neural Networks
228. ICML 2026Incomplete Multi-View Clustering via Neighborhood-Conditioned Diffusion
229. ICML 2026Information-Theoretic Disentangled Latent Modeling with Conditional Diffusion for Incomplete Multi-View Clustering
230. ICML 2026Intrinsic Task Symmetry Drives Generalization in Algorithmic Tasks
231. ICML 2026Is Task-Specific Training Necessary for Anomaly Detection?
232. ICML 2026Landmark-Guided Policy Optimization for Multi-Objective Language Model Selection
233. ICML 2026Learn to Merge: Meta-Learning for Adaptive Multi-Task Model Merging
234. ICML 2026Learning Generalized Label Distributions
235. ICML 2026Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation
236. ICML 2026LEMUR: Learned Multi-Vector Retrieval
237. ICML 2026LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning
238. ICML 2026MAGIC: Multi-Granularity Language-Informed Image Clustering
239. ICML 2026Masked Multi-path Contrast with Confidence-Gated Semantic Imputation for Incomplete Multi-view Clustering
240. ICML 2026MIMO-LP: A Multi-Input Multi-Output Framework for Subgraph-based Link Prediction
241. ICML 2026MM-Spectrum: Multimodal Multi-spectral Molecular Structural Elucidation with a Stable MoE Framework
242. ICML 2026Multi-Head Attention as a Source of Catastrophic Forgetting in MoE Transformers
243. ICML 2026Multi-Task Bayesian In-Context Learning
244. ICML 2026Multi-Task GRPO: Reliable LLM Reasoning Across Tasks
245. ICML 2026Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness, and Safety
246. ICML 2026Multi-Way Representation Alignment
247. ICML 2026Multimodal Fusion via Self-Consistent Task-Gradient Fields
248. ICML 2026NBCG: Nash-Bargained Causal Game for Long-Tailed Multi-Label NLP
249. ICML 2026Near-Optimal and Efficient First-Order Algorithm for Multi-Task Learning with Shared Linear Representation
250. ICML 2026OPTION: Optimal Transport–Guided Flow Matching for Incomplete and Unaligned 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.