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

每年论文数

各会议论文数

按年份和会议统计

多任务排序论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202356585583252
20241103867100315
2025144758094393
202617579107119480

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

全部多任务排序论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 1,440 篇，第 21 / 29 页

  1. ICLR 2024Order-Preserving GFlowNets
  2. ICLR 2024Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
  3. ICLR 2024Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
  4. ICLR 2024Robot Fleet Learning via Policy Merging
  5. ICLR 2024Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
  6. ICLR 2024Select to Perfect: Imitating desired behavior from large multi-agent data
  7. ICLR 2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
  8. ICLR 2024Tailoring Self-Rationalizers with Multi-Reward Distillation
  9. ICLR 2024Topic Modeling as Multi-Objective Contrastive Optimization
  10. ICLR 2024Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
  11. ICLR 2024Training-free Multi-objective Diffusion Model for 3D Molecule Generation
  12. ICML 2024A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization
  13. ICML 2024A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design
  14. ICML 2024Active Ranking and Matchmaking, with Perfect Matchings
  15. ICML 2024Adversarial Attacks on Combinatorial Multi-Armed Bandits
  16. ICML 2024Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs
  17. ICML 2024Applying language models to algebraic topology: generating simplicial cycles using multi-labeling in Wu's formula
  18. ICML 2024Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
  19. ICML 2024Better & Faster Large Language Models via Multi-token Prediction
  20. ICML 2024BOtied: Multi-objective Bayesian optimization with tied multivariate ranks
  21. ICML 2024Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
  22. ICML 2024Conformal Prediction for Deep Classifier via Label Ranking
  23. ICML 2024Contrasting Multiple Representations with the Multi-Marginal Matching Gap
  24. ICML 2024Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning
  25. ICML 2024DMTG: One-Shot Differentiable Multi-Task Grouping
  26. ICML 2024Efficient Pareto Manifold Learning with Low-Rank Structure
  27. ICML 2024Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization Problems
  28. ICML 2024Fair Resource Allocation in Multi-Task Learning
  29. ICML 2024Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits
  30. ICML 2024Finite-Time Convergence and Sample Complexity of Actor-Critic Multi-Objective Reinforcement Learning
  31. ICML 2024Floating Anchor Diffusion Model for Multi-motif Scaffolding
  32. ICML 2024Generalization Analysis for Multi-Label Learning
  33. ICML 2024Hard Tasks First: Multi-Task Reinforcement Learning Through Task Scheduling
  34. ICML 2024HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning
  35. ICML 2024HarmonyDream: Task Harmonization Inside World Models
  36. ICML 2024How do Transformers Perform In-Context Autoregressive Learning ?
  37. ICML 2024Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization
  38. ICML 2024Improving Transformers with Dynamically Composable Multi-Head Attention
  39. ICML 2024Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
  40. ICML 2024Leveraging (Biased) Information: Multi-armed Bandits with Offline Data
  41. ICML 2024Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning
  42. ICML 2024Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
  43. ICML 2024MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series
  44. ICML 2024MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance
  45. ICML 2024Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
  46. ICML 2024Multi-group Learning for Hierarchical Groups
  47. ICML 2024Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
  48. ICML 2024Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning
  49. ICML 2024Multi-Sender Persuasion: A Computational Perspective
  50. ICML 2024Multi-Source Conformal Inference Under Distribution Shift

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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