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 76 篇,第 1 / 2 页
- CVPR 20253D Gaussian Head Avatars with Expressive Dynamic Appearances by Compact Tensorial Representations
- CVPR 20253D Prior Is All You Need: Cross-Task Few-shot 2D Gaze Estimation
- CVPR 2025A Hubness Perspective on Representation Learning for Graph-Based Multi-View Clustering
- CVPR 2025ACAttack: Adaptive Cross Attacking RGB-T Tracker via Multi-Modal Response Decoupling
- CVPR 2025AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering
- CVPR 2025AesthetiQ: Enhancing Graphic Layout Design via Aesthetic-Aware Preference Alignment of Multi-modal Large Language Models
- CVPR 2025All-Day Multi-Camera Multi-Target Tracking
- CVPR 2025AnyDressing: Customizable Multi-Garment Virtual Dressing via Latent Diffusion Models
- CVPR 2025ASHiTA: Automatic Scene-grounded HIerarchical Task Analysis
- CVPR 2025Beyond Human Perception: Understanding Multi-Object World from Monocular View
- CVPR 2025CLOC: Contrastive Learning for Ordinal Classification with Multi-Margin N-pair Loss
- CVPR 2025Compositional Targeted Multi-Label Universal Perturbations
- CVPR 2025DAMM-Diffusion: Learning Divergence-Aware Multi-Modal Diffusion Model for Nanoparticles Distribution Prediction
- CVPR 2025Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning
- CVPR 2025Deep Fair Multi-View Clustering with Attention KAN
- CVPR 2025Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
- CVPR 2025DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations
- CVPR 2025Dynamic Integration of Task-Specific Adapters for Class Incremental Learning
- CVPR 2025EASEMVC:Efficient Dual Selection Mechanism for Deep Multi-View Clustering
- CVPR 2025ECBench: Can Multi-modal Foundation Models Understand the Egocentric World? A Holistic Embodied Cognition Benchmark
- CVPR 2025EgoLM: Multi-Modal Language Model of Egocentric Motions
- CVPR 2025Enhanced OoD Detection through Cross-Modal Alignment of Multi-Modal Representations
- CVPR 2025Enhanced then Progressive Fusion with View Graph for Multi-View Clustering
- CVPR 2025Focusing on Tracks for Online Multi-Object Tracking
- CVPR 2025Free Lunch Enhancements for Multi-modal Crowd Counting
- CVPR 2025GeoMM: On Geodesic Perspective for Multi-modal Learning
- CVPR 2025GET: Unlocking the Multi-modal Potential of CLIP for Generalized Category Discovery
- CVPR 2025Hierarchical Knowledge Prompt Tuning for Multi-task Test-Time Adaptation
- CVPR 2025Identifying and Mitigating Spurious Correlation in Multi-Task Learning
- CVPR 2025IMFine: 3D Inpainting via Geometry-guided Multi-view Refinement
- CVPR 2025Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction Tuning
- CVPR 2025Joint Scheduling of Causal Prompts and Tasks for Multi-Task Learning
- CVPR 2025KMD: Koopman Multi-modality Decomposition for Generalized Brain Tumor Segmentation under Incomplete Modalities
- CVPR 2025Large-scale Multi-view Tensor Clustering with Implicit Linear Kernels
- CVPR 2025Learning from Synchronization: Self-Supervised Uncalibrated Multi-View Person Association in Challenging Scenes
- CVPR 2025Learning to Detect Objects from Multi-Agent LiDAR Scans without Manual Labels
- CVPR 2025Less is More: Efficient Model Merging with Binary Task Switch
- CVPR 2025MangaNinja: Line Art Colorization with Precise Reference Following
- CVPR 2025MIRE: Matched Implicit Neural Representations
- CVPR 2025MLVU: Benchmarking Multi-task Long Video Understanding
- CVPR 2025MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling
- CVPR 2025MMRL: Multi-Modal Representation Learning for Vision-Language Models
- CVPR 2025MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception
- CVPR 2025MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes
- CVPR 2025Mr. DETR: Instructive Multi-Route Training for Detection Transformers
- CVPR 2025Multi-Group Proportional Representations for Text-to-Image Models
- CVPR 2025Multi-Modal Contrastive Masked Autoencoders: A Two-Stage Progressive Pre-training Approach for RGBD Datasets
- CVPR 2025Multi-Modal Synergistic Implicit Image Enhancement for Efficient Optical Flow Estimation
- CVPR 2025Multi-modal Topology-embedded Graph Learning for Spatially Resolved Genes Prediction from Pathology Images with Prior Gene Similarity Information
- CVPR 2025Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representation
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。