多任务排序论文趋势 2023–2026
多目标排序
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,440 篇被归入该主题的论文。
主要结论
- 多任务排序论文从 2023 年的 252 篇增长到 2026 年的 480 篇，三年间扩大到约 1.9 倍。
- NeurIPS 是发多任务排序论文最多的会议，2023–2026 年共 485 篇，占四个会议总量的 34%。
- 交叉方向里涨得最快的是AI 智能体：同时属于两个主题的论文从 2023 年的 8 篇增至 2026 年的 52 篇。
- 在「推荐与广告」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的点击率预测是 2.6 倍，多任务排序是 1.9 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 56 | 58 | 55 | 83 | 252 |
| 2024 | 110 | 38 | 67 | 100 | 315 |
| 2025 | 144 | 75 | 80 | 94 | 393 |
| 2026 | 175 | 79 | 107 | 119 | 480 |
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 2026Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings
- ICLR 2026Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?
- CVPR 2026A Supervised Multi-task Framework for Joint cryo-ET Restoration Enabled by
- 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 2025Balanced Ranking with Relative Centrality: A multi-core periphery perspective
- 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 2024Order-Preserving GFlowNets
- CVPR 2024Domain Separation Graph Neural Networks for Saliency Object Ranking
- NeurIPS 2023AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three Weeks
- ICML 2023Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information
- 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 2026Dataless Weight Disentanglement in Task Arithmetic via Kronecker-Factored Approximate Curvature
- CVPR 2026Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers
全部多任务排序论文
共 480 篇，第 10 / 10 页
- NeurIPS 2026SelfGuard: Self-Supervised Deviation Modeling for Multi-Modal Jailbreak Detection
- NeurIPS 2026Sequence-to-Sequence Modeling with Camera-Induced Priors for Multi-View Stereo
- NeurIPS 2026Simple Extensions of Single-Objective Acquisition Functions and Hedge Strategies for Multi-Objective Bayesian Optimization
- NeurIPS 2026SING-CH: Task-Scale-Agnostic Lifelong Cross-Modal Hashing on Statistical Manifolds
- NeurIPS 2026SMOG: Scalable Meta-Learning for Multi-Objective Bayesian Optimization
- NeurIPS 2026SpecBridge: Learning Natural-Language Formalization Plans for the Formal Specification Synthesis Task
- NeurIPS 2026SpecHop: Continuous Speculation for Accelerating Multi-Hop Retrieval Agents
- NeurIPS 2026Spectral-Spatial Interpretation
- NeurIPS 2026Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation
- NeurIPS 2026Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation
- NeurIPS 2026STEP: Learning STructured Embeddings for Progressive Time Series
- NeurIPS 2026Structurally Separated DAG Learning with Multi-Scale Normalized Closure
- NeurIPS 2026Surface Recovery Is Not State Recovery: Pressure–Recovery–Relapse in Multi-turn LLMs
- NeurIPS 2026Sustainability in the Loop: AI Model Development Should Be Multi-Objective
- NeurIPS 2026SyncLight: Single-Edit Multi-View Relighting
- NeurIPS 2026TAPIOCA: Why Task- Aware Pruning Improves OOD model Capability
- NeurIPS 2026Task-Aware KV Cache Compression for LLM Agents via Utility-Driven Step Pruning
- NeurIPS 2026The End Justifies the Mean: Linear Ranking Rules for Proportional Sequential Decisions
- NeurIPS 2026TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing
- NeurIPS 2026Towards High Semantic Fidelity: Hyperdimensional Symbolic Messages in Multi-Agent Communication
- NeurIPS 2026Train the Agent, Not the Expert: Learning to Harness Heterogeneous Experts for Multi-Turn Visual Reasoning
- NeurIPS 2026Truthful Calibration Errors for Multi-Class Prediction
- NeurIPS 2026U-MOF: Uncertainty-Guided Parameter-Efficient Multi-Objective Fine-Tuning for Long-Tailed Recognition
- NeurIPS 2026UGM: Unified Multi-scale Genomic Event Modeling with Site-level Joint Prediction
- NeurIPS 2026Unified Resource-Grounded Coordination Protocol for Orchestrator-Free Heterogeneous Multi-Agent Systems
- NeurIPS 2026ViewSAM: Learning View-aware Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking
- NeurIPS 2026Virtual Task Prompting for Multi-Task Scene Understanding
- NeurIPS 2026When Attention Closes: How LLMs Lose the Thread in Multi-Turn Interaction
- NeurIPS 2026When Does Non-Uniform Replay Matter in Reinforcement Learning?
- NeurIPS 2026When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding
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 查多任务排序在 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-ranking"}
常见问题
- 2023–2026 年四大会议一共有多少篇多任务排序论文？
- 共 1,440 篇，按年份分别是 2023 年 252 篇、2024 年 315 篇、2025 年 393 篇、2026 年 480 篇。
- NeurIPS 2026 有多少篇多任务排序论文？
- NeurIPS 2026 有 175 篇多任务排序论文，上一届是 144 篇。
- ICLR 2026 有多少篇多任务排序论文？
- ICLR 2026 有 79 篇多任务排序论文，上一届是 75 篇。
- ICML 2026 有多少篇多任务排序论文？
- ICML 2026 有 107 篇多任务排序论文，上一届是 80 篇。
- CVPR 2026 有多少篇多任务排序论文？
- CVPR 2026 有 119 篇多任务排序论文，上一届是 94 篇。
- 哪个会议的多任务排序论文最多？
- NeurIPS，2023–2026 年共 485 篇。