多任务学习论文趋势 2023–2026
共享表示
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,181 篇被归入该主题的论文。
主要结论
- 多任务学习论文从 2023 年的 288 篇增长到 2026 年的 402 篇，三年间扩大到约 1.4 倍。
- NeurIPS 是发多任务学习论文最多的会议，2023–2026 年共 399 篇，占四个会议总量的 34%。
- 交叉方向里涨得最快的是数据集与基准：同时属于两个主题的论文从 2023 年的 6 篇增至 2026 年的 16 篇。
- 在「元学习与迁移」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的基础模型适配是 3.8 倍，多任务学习是 1.4 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 111 | 43 | 52 | 82 | 288 |
| 2024 | 61 | 31 | 58 | 77 | 227 |
| 2025 | 101 | 40 | 47 | 76 | 264 |
| 2026 | 126 | 57 | 91 | 128 | 402 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- 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
全部多任务学习论文
共 264 篇，第 6 / 6 页
- NeurIPS 2025Scaling Image Geo-Localization to Continent Level
- NeurIPS 2025SIFusion: A Unified Fusion Framework for Multi-granularity Arctic Sea Ice Forecasting
- NeurIPS 2025Single GPU Task Adaptation of Pathology Foundation Models for Whole Slide Image Analysis
- NeurIPS 2025SMARTraj$^2$: A Stable Multi-City Adaptive Method for Multi-View Spatio-Temporal Trajectory Representation Learning
- NeurIPS 2025Soft Task-Aware Routing of Experts for Equivariant Representation Learning
- NeurIPS 2025SynCL: A Synergistic Training Strategy with Instance-Aware Contrastive Learning for End-to-End Multi-Camera 3D Tracking
- NeurIPS 2025Task-Optimized Convolutional Recurrent Networks Align with Tactile Processing in the Rodent Brain
- NeurIPS 2025Task-Specific Data Selection for Instruction Tuning via Monosemantic Neuronal Activations
- NeurIPS 2025Theory-Driven Label-Specific Representation for Incomplete Multi-View Multi-Label Learning
- NeurIPS 2025Towards Minimizing Feature Drift in Model Merging: Layer-wise Task Vector Fusion for Adaptive Knowledge Integration
- NeurIPS 2025TS-MOF: Two-Stage Multi-Objective Fine-tuning for Long-Tailed Recognition
- NeurIPS 2025Unbiased Prototype Consistency Learning for Multi-Modal and Multi-Task Object Re-Identification
- NeurIPS 2025VaMP: Variational Multi-Modal Prompt Learning for Vision-Language Models
- NeurIPS 2025Where Graph Meets Heterogeneity: Multi-View Collaborative Graph Experts
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查多任务学习在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "multi-task-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇多任务学习论文？
- 共 1,181 篇，按年份分别是 2023 年 288 篇、2024 年 227 篇、2025 年 264 篇、2026 年 402 篇。
- NeurIPS 2026 有多少篇多任务学习论文？
- NeurIPS 2026 有 126 篇多任务学习论文，上一届是 101 篇。
- ICLR 2026 有多少篇多任务学习论文？
- ICLR 2026 有 57 篇多任务学习论文，上一届是 40 篇。
- ICML 2026 有多少篇多任务学习论文？
- ICML 2026 有 91 篇多任务学习论文，上一届是 47 篇。
- CVPR 2026 有多少篇多任务学习论文？
- CVPR 2026 有 128 篇多任务学习论文，上一届是 76 篇。
- 哪个会议的多任务学习论文最多？
- NeurIPS，2023–2026 年共 399 篇。