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 288 篇，第 6 / 6 页
- NeurIPS 2023Multi-task learning with summary statistics
- NeurIPS 2023Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
- NeurIPS 2023MultiMoDN—Multimodal, Multi-Task, Interpretable Modular Networks
- NeurIPS 2023Mutual-Information Regularized Multi-Agent Policy Iteration
- NeurIPS 2023Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning
- NeurIPS 2023Nonparametric Identifiability of Causal Representations from Unknown Interventions
- NeurIPS 2023Online Pricing for Multi-User Multi-Item Markets
- NeurIPS 2023Optimistic Rates for Multi-Task Representation Learning
- NeurIPS 2023Partial Multi-Label Learning with Probabilistic Graphical Disambiguation
- NeurIPS 2023Pengi: An Audio Language Model for Audio Tasks
- NeurIPS 2023Prediction and Control in Continual Reinforcement Learning
- NeurIPS 2023ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion
- NeurIPS 2023RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency
- NeurIPS 2023Real-World Image Super-Resolution as Multi-Task Learning
- NeurIPS 2023Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
- NeurIPS 2023Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach
- NeurIPS 2023Revisiting Scalarization in Multi-Task Learning: A Theoretical Perspective
- NeurIPS 2023RoboHive: A Unified Framework for Robot Learning
- NeurIPS 2023Robust Concept Erasure via Kernelized Rate-Distortion Maximization
- NeurIPS 2023Scalarization for Multi-Task and Multi-Domain Learning at Scale
- NeurIPS 2023Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
- NeurIPS 2023SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
- NeurIPS 2023SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
- NeurIPS 2023STXD: Structural and Temporal Cross-Modal Distillation for Multi-View 3D Object Detection
- NeurIPS 2023Task-aware Distributed Source Coding under Dynamic Bandwidth
- NeurIPS 2023Task-Robust Pre-Training for Worst-Case Downstream Adaptation
- NeurIPS 2023TaskMet: Task-driven Metric Learning for Model Learning
- NeurIPS 2023The Simplicity Bias in Multi-Task RNNs: Shared Attractors, Reuse of Dynamics, and Geometric Representation
- NeurIPS 2023TOA: Task-oriented Active VQA
- NeurIPS 2023Towards a Unified Framework of Contrastive Learning for Disentangled Representations
- NeurIPS 2023Tuning Multi-mode Token-level Prompt Alignment across Modalities
- NeurIPS 2023Universal Online Learning with Gradient Variations: A Multi-layer Online Ensemble Approach
- NeurIPS 2023Unpaired Multi-Domain Causal Representation Learning
- NeurIPS 2023Video-Mined Task Graphs for Keystep Recognition in Instructional Videos
- NeurIPS 2023Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
- NeurIPS 2023VoxDet: Voxel Learning for Novel Instance Detection
- NeurIPS 2023Weakly-Supervised Concealed Object Segmentation with SAM-based Pseudo Labeling and Multi-scale Feature Grouping
- NeurIPS 2023When Can We Track Significant Preference Shifts in Dueling Bandits?
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。