序列推荐论文趋势 2023–2026

主要结论

• 序列推荐论文从 2023 年的 39 篇增长到 2026 年的 43 篇，三年间扩大到约 1.1 倍。
• NeurIPS 是发序列推荐论文最多的会议，2023–2026 年共 67 篇，占四个会议总量的 47%。
• 交叉方向里涨得最快的是MCTS：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 5 篇。
• 在「推荐与广告」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的点击率预测是 2.6 倍，序列推荐是 1.1 倍。

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 2026An Embarrassingly Simple Graph Heuristic Reveals Shortcut-Solvable Benchmarks for Sequential Recommendation
• ICML 2026Sequential Group Composition: A Window into the Mechanics of Deep Learning
• ICLR 2026Energy-Regularized Sequential Model Editing on Hyperspheres
• CVPR 2026Online3R Online Learning for Consistent Sequential Reconstruction Based on Geometry
• NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
• ICML 2025A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings
• ICLR 2025A Non-Contrastive Learning Framework for Sequential Recommendation with Preference-Preserving Profile Generation
• NeurIPS 2024CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence
• ICML 2024Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
• ICLR 2024Parallelizing non-linear sequential models over the sequence length
• CVPR 2024MuseChat: A Conversational Music Recommendation System for Videos
• NeurIPS 2023Cascading Bandits: Optimizing Recommendation Frequency in Delayed Feedback Environments
• ICML 2023A Kernel Stein Test of Goodness of Fit for Sequential Models
• ICLR 2023Neural-based classification rule learning for sequential data
• CVPR 2023Guided Recommendation for Model Fine-Tuning
• NeurIPS 2026DARTS: Targeting Prognostic Covariates in Budget-Constrained Sequential Experiments
• ICML 2026Asymptotically Optimal Sequential Testing with Markovian Data
• ICLR 2026Sequential Parallel Duality in Prefix Scannable Models
• CVPR 2026MGDHand Multi-Granularity Prior-to-Inertial Distillation Framework for Sequential 3D Hand Pose
• NeurIPS 2025FFN Fusion: Rethinking Sequential Computation in Large Language Models

全部序列推荐论文

共 142 篇，第 2 / 3 页

51. ICML 2025Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
52. ICML 2025MTSTRec: Multimodal Time-Aligned Shared Token Recommender
53. ICML 2025Training High Performance Spiking Neural Network by Temporal Model Calibration
54. NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
55. NeurIPS 2025FFN Fusion: Rethinking Sequential Computation in Large Language Models
56. NeurIPS 2025Hippocampal-like Sequential Editing for Continual Knowledge Updates in Large Language Models
57. NeurIPS 2025How Patterns Dictate Learnability in Sequential Data
58. NeurIPS 2025HPSERec: A Hierarchical Partitioning and Stepwise Enhancement Framework for Long-tailed Sequential Recommendation
59. NeurIPS 2025Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm
60. NeurIPS 2025Martingale Posterior Neural Networks for Fast Sequential Decision Making
61. NeurIPS 2025Merging on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging
62. NeurIPS 2025P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models
63. NeurIPS 2025Path-Enhanced Contrastive Learning for Recommendation
64. NeurIPS 2025Personalized Exercise Recommendation with Semantically-Grounded Knowledge Tracing
65. NeurIPS 2025Photography Perspective Composition: Towards Aesthetic Perspective Recommendation
66. NeurIPS 2025Sequential Attention-based Sampling for Histopathological Analysis
67. NeurIPS 2025SPOT-Trip: Dual-Preference Driven Out-of-Town Trip Recommendation
68. NeurIPS 2025SRA-CL: Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation
69. NeurIPS 2025STAR-Bets: Sequential TArget-Recalculating Bets for Tighter Confidence Intervals
70. NeurIPS 2025Tree of Preferences for Diversified Recommendation
71. NeurIPS 2025TV-Rec: Time-Variant Convolutional Filter for Sequential Recommendation
72. NeurIPS 2025YEAST: Yet Another Sequential Test
73. CVPR 2024MuseChat: A Conversational Music Recommendation System for Videos
74. ICLR 2024Federated Recommendation with Additive Personalization
75. ICLR 2024Function-space Parameterization of Neural Networks for Sequential Learning
76. ICLR 2024Parallelizing non-linear sequential models over the sequence length
77. ICLR 2024Progressive Fourier Neural Representation for Sequential Video Compilation
78. ICML 2024Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations
79. ICML 2024Break the Sequential Dependency of LLM Inference Using Lookahead Decoding
80. ICML 2024On the Embedding Collapse when Scaling up Recommendation Models
81. ICML 2024On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation
82. ICML 2024Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams
83. ICML 2024Pursuing Overall Welfare in Federated Learning through Sequential Decision Making
84. ICML 2024Reducing sequential change detection to sequential estimation
85. ICML 2024Sequential Disentanglement by Extracting Static Information From A Single Sequence Element
86. ICML 2024Sequential Kernel Goodness-of-fit Testing
87. ICML 2024Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
88. ICML 2024Wukong: Towards a Scaling Law for Large-Scale Recommendation
89. NeurIPS 2024A distributional simplicity bias in the learning dynamics of transformers
90. NeurIPS 2024Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists
91. NeurIPS 2024Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model
92. NeurIPS 2024Complete Graphical Criterion for Sequential Covariate Adjustment in Causal Inference
93. NeurIPS 2024CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence
94. NeurIPS 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendation
95. NeurIPS 2024End-to-end Learnable Clustering for Intent Learning in Recommendation
96. NeurIPS 2024Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation
97. NeurIPS 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation
98. NeurIPS 2024On Softmax Direct Preference Optimization for Recommendation
99. NeurIPS 2024Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss
100. NeurIPS 2024Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity

常见问题

2023–2026 年四大会议一共有多少篇序列推荐论文？

共 142 篇，按年份分别是 2023 年 39 篇、2024 年 31 篇、2025 年 29 篇、2026 年 43 篇。

NeurIPS 2026 有多少篇序列推荐论文？

NeurIPS 2026 有 20 篇序列推荐论文，上一届是 19 篇。

ICLR 2026 有多少篇序列推荐论文？

ICLR 2026 有 10 篇序列推荐论文，上一届是 6 篇。

ICML 2026 有多少篇序列推荐论文？

ICML 2026 有 11 篇序列推荐论文，上一届是 4 篇。

CVPR 2026 有多少篇序列推荐论文？

CVPR 2026 有 2 篇序列推荐论文。

哪个会议的序列推荐论文最多？

NeurIPS，2023–2026 年共 67 篇。