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

399 papers, page 3 of 8

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
127. NeurIPS 2025$i$MIND: Insightful Multi-subject Invariant Neural Decoding
128. NeurIPS 2025A Data-Driven Prism: Multi-View Source Separation with Diffusion Model Priors
129. NeurIPS 2025A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
130. NeurIPS 2025A Minimalistic Unified Framework for Incremental Learning across Image Restoration Tasks
131. NeurIPS 2025A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
132. NeurIPS 2025Adaptable Safe Policy Learning from Multi-task Data with Constraint Prioritized Decision Transformer
133. NeurIPS 2025AF-UMC: An Alignment-Free Fusion Framework for Unaligned Multi-View Clustering
134. NeurIPS 2025Are Greedy Task Orderings Better Than Random in Continual Linear Regression?
135. NeurIPS 2025Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners
136. NeurIPS 2025Bit-swapping Oriented Twin-memory Multi-view Clustering in Lifelong Incomplete Scenarios
137. NeurIPS 2025Cameras as Relative Positional Encoding
138. NeurIPS 2025Can Class-Priors Help Single-Positive Multi-Label Learning?
139. NeurIPS 2025Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?
140. NeurIPS 2025Confidence-Aware With Prototype Alignment for Partial Multi-label Learning
141. NeurIPS 2025Connecting Neural Models Latent Geometries with Relative Geodesic Representations
142. NeurIPS 2025Constructing an Optimal Behavior Basis for the Option Keyboard
143. NeurIPS 2025Continual Model Merging without Data: Dual Projections for Balancing Stability and Plasticity
144. NeurIPS 2025Continual Optimization with Symmetry Teleportation for Multi-Task Learning
145. NeurIPS 2025Contribution of task-irrelevant stimuli to drift of neural representations
146. NeurIPS 2025CSI-Bench: A Large-Scale In-the-Wild Dataset for Multi-task WiFi Sensing
147. NeurIPS 2025DeepASA: An Object-Oriented Multi-Purpose Network for Auditory Scene Analysis
148. NeurIPS 2025DICEPTION: A Generalist Diffusion Model for Visual Perceptual Tasks
149. NeurIPS 2025DINO-Foresight: Looking into the Future with DINO
150. NeurIPS 2025Diversity-oriented Deep Multi-modal 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.