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

402 papers, page 7 of 9

301. NeurIPS 2026CoDeRNet: Selective Cross-Task Routing under Heterogeneous Supervision for Change Detection and Captioning
302. NeurIPS 2026Compressible Representations: Functional Spines in Deep Neural Networks
303. NeurIPS 2026Constructive Neural Policies for the Quadratic Assignment Problem via Multi-Expert Imitation
304. NeurIPS 2026Cross-Family Universality of Behavioral Axes via Anchor-Projected Representations
305. NeurIPS 2026Cross-User Poisoning: User-Task Boundary Failures in Multi-User Collaborative Language Agents
306. NeurIPS 2026Crowded in B-Space: Calibrating Shared Directions for LoRA Merging
307. NeurIPS 2026Curvature-Guided Parameter Initialization for Multi-Task Learning
308. NeurIPS 2026Cyclic Discrete Diffusion: A Novel Multi-Class Segmentation Refinement Technique
309. NeurIPS 2026DC-ViT: Modulating Spatial and Channel Interactions for Multi-Channel Images
310. NeurIPS 2026DDMS: Discriminative Distillation of Multi-view Foundational Features into Single-view Models
311. NeurIPS 2026Decomposed Representations Mitigate the Alignment–Specificity Trade-off in Multi-Omics
312. NeurIPS 2026Deconstructing Multi-Task Active Learning: The Paradox of Gradient Conflict and Orthogonal Decomposition
313. NeurIPS 2026Delve into the Applicability of Advanced Optimizers for Multi-Task Learning
314. NeurIPS 2026Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning
315. NeurIPS 2026Distributionally Robust Multi-Task Reinforcement Learning via Adaptive Task Sampling
316. NeurIPS 2026Driver Attention as Competitive Allocation: A Scene--Task-Aware Dual-Branch Framework
317. NeurIPS 2026EEG Benchmarking Needs a Task Specification Layer: NeuroDoc for Rulebook-Guided, Executable Benchmark Construction
318. NeurIPS 2026Efficient SAM 3 Adaptation for Multi-Class Semantic Segmentation via Dense Competitive Representations
319. NeurIPS 2026Elastic Representations via Hyperbolic Geometry
320. NeurIPS 2026Exponential Map Models as an Interpretable Framework for Generating Neural Spatial Representations
321. NeurIPS 2026Focusable Monocular Depth Estimation
322. NeurIPS 2026From Isolated feature to Orbits:\\Discovering Music Concepts via Multi-SAE Alignment
323. NeurIPS 2026Frontier Task Synthesis Via Solution-Centric Evolution
324. NeurIPS 2026Grouped Adaptive Head Mixing for Personalized Multi-Task Federated Reinforcement Learning
325. NeurIPS 2026Harder the Task, Sparser the Representation: Sparsity as a Learning Signature of Capability in LLMs
326. NeurIPS 2026How are linear representations learned? Exact solutions to the dynamics of abstraction
327. NeurIPS 2026How Data Augmentation Shapes Neural Representations
328. NeurIPS 2026HRIL: Isolating Multimodal Synergy via Higher-Order Dependence
329. NeurIPS 2026Hydra: Towards Transferable Multi-Task Learning on Temporal Graphs
330. NeurIPS 2026HyperSkill: Multi-Modal Skill Learning on the Unit Hypersphere
331. NeurIPS 2026Individuals Matter: Improving Deep Multi-View Clustering via Explicit Single-View Enhancement
332. NeurIPS 2026Insight-Driven Search: A Framework for Multi-objective Automated Heuristic Design with Large Language Models
333. NeurIPS 2026InTAct: Interval-based Task Activation Consolidation for Continual Learning
334. NeurIPS 2026Iterative ILP with Update-Size Control for Reducing Surrogate-Task Mismatch in Bit-Width Selection
335. NeurIPS 2026Justitia: Fair and Efficient Scheduling of Task-parallel LLM Agents with Selective Pampering
336. NeurIPS 2026Laplacian Heads Improve Transformers by Smoothing Token Representations
337. NeurIPS 2026Learning Interpretable Switching Dynamics in Shared Neural-Behavioral Latent Space
338. NeurIPS 2026Learning Task-Centric World Models from Visual Foundations
339. NeurIPS 2026Learning What to Predict: Downstream-Guided Task Design for Continued Pretraining
340. NeurIPS 2026LoRASpace: A Pool-Wide Shared Substrate for Static and Dynamic Multi-LoRA Composition
341. NeurIPS 2026MAdam: Metric-Aware Multi-Objective Adam
342. NeurIPS 2026MAGE: Towards Generalizable Multi-timescale EEG Representations
343. NeurIPS 2026MaRiO: Multi-agent Collaborative Reasoning via Shared Observations in MLLMs
344. NeurIPS 2026Market-Based Runtime Resource Allocation for LLM Multi-Agent Systems
345. NeurIPS 2026Markov Metrical Task Systems
346. NeurIPS 2026MC-H: Multi-Granularity Clustering with Hyperspherical Determinantal Point Process
347. NeurIPS 2026MCAS: Signal-Processing-Based Multi-View Contrastive Learning for Acoustic Sensing
348. NeurIPS 2026Measuring AI Agents' Progress on Multi-Step Cyber Attack Scenarios
349. NeurIPS 2026Mitigating Reward Hacking via Task Representations
350. NeurIPS 2026MLLM Makes Strong Backbone for Multi-Modal Object Detection

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.