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

126 papers, page 3 of 3

101. NeurIPS 2026S²MoE: Shared-Subspace Mixture of Sparse Experts
102. NeurIPS 2026SCION: Scene Composition via Instanced Neural Primitives
103. NeurIPS 2026SelfGuard: Self-Supervised Deviation Modeling for Multi-Modal Jailbreak Detection
104. NeurIPS 2026Sequence-to-Sequence Modeling with Camera-Induced Priors for Multi-View Stereo
105. NeurIPS 2026Serialization Tax in Shared-Latent Exchangeable Decisions
106. NeurIPS 2026SMOG: Scalable Meta-Learning for Multi-Objective Bayesian Optimization
107. NeurIPS 2026SpanFormer: Multi-Level Adaptive Sparsity for Object Detection in High-Resolution Wide Shots
108. NeurIPS 2026SpecBridge: Learning Natural-Language Formalization Plans for the Formal Specification Synthesis Task
109. NeurIPS 2026SpecHop: Continuous Speculation for Accelerating Multi-Hop Retrieval Agents
110. NeurIPS 2026Spectral Alignment in Forward–Backward Representations via Temporal Abstraction
111. NeurIPS 2026Spectral Insights from the Unconstrained Feature Model for Neural Multi-Output Regression
112. NeurIPS 2026Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation
113. NeurIPS 2026Structurally Separated DAG Learning with Multi-Scale Normalized Closure
114. NeurIPS 2026Sustainability in the Loop: AI Model Development Should Be Multi-Objective
115. NeurIPS 2026SyncLight: Single-Edit Multi-View Relighting
116. NeurIPS 2026TAPIOCA: Why Task- Aware Pruning Improves OOD model Capability
117. NeurIPS 2026The Alignment Illusion in Multimodal Large Language Models
118. NeurIPS 2026The Ringelmann Effect in Multi-Agent LLM Systems: A Scaling Law for Effective Team Size
119. NeurIPS 2026TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing
120. NeurIPS 2026TraceGuard: Defending Multi-Turn Jailbreak Attacks via Prompt-Response Risk Signal Tracking
121. NeurIPS 2026UniReFP: Robust Unified Fingerprinting for Vision Models against Cross-Task Repurposing Attacks
122. NeurIPS 2026ViewSAM: Learning View-aware Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking
123. NeurIPS 2026Virtual Task Prompting for Multi-Task Scene Understanding
124. NeurIPS 2026When Attention Closes: How LLMs Lose the Thread in Multi-Turn Interaction
125. NeurIPS 2026When Do Learned State Representations Break Sensitivity Analysis?
126. NeurIPS 2026When Do Multi-Agent Systems Help? An Information Bottleneck Perspective

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.