学习排序论文趋势 2023–2026

主要结论

• 学习排序论文从 2023 年的 142 篇降到 2026 年的 55 篇，热度在回落。
• NeurIPS 是发学习排序论文最多的会议，2023–2026 年共 154 篇，占四个会议总量的 60%。
• 交叉方向里涨得最快的是低秩适配：同时属于两个主题的论文从 2023 年的 39 篇增至 2026 年的 43 篇。
• 在「信息检索」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的交叉编码重排是 3.0 倍，学习排序是 0.4 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 2026Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank
• ICML 2026From Per-Image Low-Rank to Encoding Mismatch: Rethinking Feature Distillation in Vision Transformers
• ICLR 2026Designing Rules to Pick a Rule: Aggregation by Consistency
• CVPR 2026LRDUN A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive
• NeurIPS 2025From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics
• ICML 2025Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
• ICLR 2025Palu: KV-Cache Compression with Low-Rank Projection
• CVPR 2025Breaking the Low-Rank Dilemma of Linear Attention
• NeurIPS 2024Efficient LLM Scheduling by Learning to Rank
• ICML 2024Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
• ICLR 2024LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
• CVPR 2024Tuning Stable Rank Shrinkage: Aiming at the Overlooked Structural Risk in Fine-tuning
• NeurIPS 2023A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
• ICML 2023Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning
• ICLR 2023Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
• CVPR 20231% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions
• NeurIPS 2026Matrix Recovery Via Symmetric Rank-one Measurements With Random Unit-modulus Vectors
• ICML 2026The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms
• ICLR 2026Revisiting Weight Regularization for Low-Rank Continual Learning
• CVPR 2026Low-Rank Residual Diffusion Models

全部学习排序论文

共 28 篇，第 1 / 1 页

1. CVPR 2024LORS: Low-rank Residual Structure for Parameter-Efficient Network Stacking
2. CVPR 2024PELA: Learning Parameter-Efficient Models with Low-Rank Approximation
3. CVPR 2024Tuning Stable Rank Shrinkage: Aiming at the Overlooked Structural Risk in Fine-tuning
4. ICLR 2024LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
5. ICLR 2024Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming
6. ICML 2024Efficient Pareto Manifold Learning with Low-Rank Structure
7. ICML 2024Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
8. ICML 2024FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
9. ICML 2024Flora: Low-Rank Adapters Are Secretly Gradient Compressors
10. ICML 2024GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
11. ICML 2024High-Dimensional Geometric Streaming for Nearly Low Rank Data
12. ICML 2024Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
13. ICML 2024Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
14. ICML 2024LQER: Low-Rank Quantization Error Reconstruction for LLMs
15. ICML 2024Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
16. ICML 2024Operator SVD with Neural Networks via Nested Low-Rank Approximation
17. ICML 2024Reweighted Solutions for Weighted Low Rank Approximation
18. NeurIPS 2024Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models
19. NeurIPS 2024Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models
20. NeurIPS 2024Efficient LLM Scheduling by Learning to Rank
21. NeurIPS 2024Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
22. NeurIPS 2024Entrywise error bounds for low-rank approximations of kernel matrices
23. NeurIPS 2024Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
24. NeurIPS 2024Loki: Low-rank Keys for Efficient Sparse Attention
25. NeurIPS 2024Neural Embeddings Rank: Aligning 3D latent dynamics with movements
26. NeurIPS 2024SGD vs GD: Rank Deficiency in Linear Networks
27. NeurIPS 2024Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning
28. NeurIPS 2024Weight decay induces low-rank attention layers

常见问题

2023–2026 年四大会议一共有多少篇学习排序论文？

共 257 篇，按年份分别是 2023 年 142 篇、2024 年 28 篇、2025 年 32 篇、2026 年 55 篇。

NeurIPS 2026 有多少篇学习排序论文？

NeurIPS 2026 有 18 篇学习排序论文，上一届是 13 篇。

ICLR 2026 有多少篇学习排序论文？

ICLR 2026 有 9 篇学习排序论文，上一届是 8 篇。

ICML 2026 有多少篇学习排序论文？

ICML 2026 有 26 篇学习排序论文，上一届是 10 篇。

CVPR 2026 有多少篇学习排序论文？

CVPR 2026 有 2 篇学习排序论文，上一届是 1 篇。

哪个会议的学习排序论文最多？

NeurIPS，2023–2026 年共 154 篇。