低秩适配论文趋势 2023–2026

主要结论

• 低秩适配论文从 2023 年的 282 篇增长到 2026 年的 841 篇，三年间扩大到约 3.0 倍。
• NeurIPS 是发低秩适配论文最多的会议，2023–2026 年共 781 篇，占四个会议总量的 34%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 4 篇增至 2026 年的 61 篇。
• 在「优化与缩放」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的缩放定律是 4.1 倍，低秩适配是 3.0 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 2026$\delta$-Mem: : Efficient Online Memory For Large Language Models
• ICML 2026A3: an Analytical Low-Rank Approximation Framework for Attention
• ICLR 2026A Guardrail for Safety Preservation: When Safety-Sensitive Subspace Meets Harmful-Resistant Null-Space
• CVPR 20262-Shots in the Dark Low-Light Denoising with Minimal Data Acquisition
• NeurIPS 2025A geometric framework for momentum-based optimizers for low-rank training
• ICML 2025Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
• ICLR 2025A Quantum Circuit-Based Compression Perspective for Parameter-Efficient Learning
• CVPR 2025AdaDARE-gamma: Balancing Stability and Plasticity in Multi-modal LLMs through Efficient Adaptation
• NeurIPS 2024Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
• ICML 2024A Tensor Decomposition Perspective on Second-order RNNs
• ICLR 2024A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
• CVPR 2024DePT: Decoupled Prompt Tuning
• NeurIPS 2023A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression
• ICML 2023A Three-regime Model of Network Pruning
• ICLR 2023A General Rank Preserving Framework for Asymmetric Image Retrieval
• CVPR 20231% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions
• NeurIPS 2026A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction
• ICML 2026Adaptive Utilization of Low-Rank Adaptation via Conditioned Gating
• ICLR 2026ABBA-Adapters: Efficient and Expressive Fine-Tuning of Foundation Models
• CVPR 2026Basis-Oriented Low-rank Transfer for Few-Shot and Test-Time Adaptation

全部低秩适配论文

共 565 篇，第 11 / 12 页

501. ICML 2023A Three-regime Model of Network Pruning
502. ICML 2023Adversarial Parameter Attack on Deep Neural Networks
503. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
504. ICML 2023Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions
505. ICML 2023Bootstrap in High Dimension with Low Computation
506. ICML 2023Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models
507. ICML 2023Curious Replay for Model-based Adaptation
508. ICML 2023Data Efficient Neural Scaling Law via Model Reusing
509. ICML 2023Diffusion Models are Minimax Optimal Distribution Estimators
510. ICML 2023Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning
511. ICML 2023DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
512. ICML 2023Domain Adaptation for Time Series Under Feature and Label Shifts
513. ICML 2023Double-Weighting for Covariate Shift Adaptation
514. ICML 2023Efficient List-Decodable Regression using Batches
515. ICML 2023Efficient Personalized Federated Learning via Sparse Model-Adaptation
516. ICML 2023ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models
517. ICML 2023Exploring the Benefits of Training Expert Language Models over Instruction Tuning
518. ICML 2023Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization
519. ICML 2023Flash: Concept Drift Adaptation in Federated Learning
520. ICML 2023Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost
521. ICML 2023Geometric Autoencoders - What You See is What You Decode
522. ICML 2023Hierarchical Imitation Learning with Vector Quantized Models
523. ICML 2023Human-Timescale Adaptation in an Open-Ended Task Space
524. ICML 2023HyperTuning: Toward Adapting Large Language Models without Back-propagation
525. ICML 2023Improved Algorithms for White-Box Adversarial Streams
526. ICML 2023In Search for a Generalizable Method for Source Free Domain Adaptation
527. ICML 2023Last Switch Dependent Bandits with Monotone Payoff Functions
528. ICML 2023Learning in POMDPs is Sample-Efficient with Hindsight Observability
529. ICML 2023Learning-Rate-Free Learning by D-Adaptation
530. ICML 2023LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
531. ICML 2023Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-Single
532. ICML 2023Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning
533. ICML 2023Mechanistic Mode Connectivity
534. ICML 2023Multi-User Reinforcement Learning with Low Rank Rewards
535. ICML 2023Naive imputation implicitly regularizes high-dimensional linear models
536. ICML 2023NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning
537. ICML 2023Offline Meta Reinforcement Learning with In-Distribution Online Adaptation
538. ICML 2023On Balancing Bias and Variance in Unsupervised Multi-Source-Free Domain Adaptation
539. ICML 2023On Pitfalls of Test-Time Adaptation
540. ICML 2023On the Role of Attention in Prompt-tuning
541. ICML 2023One-sided Matrix Completion from Two Observations Per Row
542. ICML 2023Over-parametrization via Lifting for Low-rank Matrix Sensing: Conversion of Spurious Solutions to Strict Saddle Points
543. ICML 2023Provable Dynamic Fusion for Low-Quality Multimodal Data
544. ICML 2023Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
545. ICML 2023Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption
546. ICML 2023RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
547. ICML 2023Reinforcement Learning Can Be More Efficient with Multiple Rewards
548. ICML 2023Reinforcement Learning in Low-rank MDPs with Density Features
549. ICML 2023RLSbench: Domain Adaptation Under Relaxed Label Shift
550. ICML 2023Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch

常见问题

2023–2026 年四大会议一共有多少篇低秩适配论文？

共 2,273 篇，按年份分别是 2023 年 282 篇、2024 年 518 篇、2025 年 632 篇、2026 年 841 篇。

NeurIPS 2026 有多少篇低秩适配论文？

NeurIPS 2026 有 269 篇低秩适配论文，上一届是 241 篇。

ICLR 2026 有多少篇低秩适配论文？

ICLR 2026 有 184 篇低秩适配论文，上一届是 152 篇。

ICML 2026 有多少篇低秩适配论文？

ICML 2026 有 240 篇低秩适配论文，上一届是 136 篇。

CVPR 2026 有多少篇低秩适配论文？

CVPR 2026 有 148 篇低秩适配论文，上一届是 103 篇。

哪个会议的低秩适配论文最多？

NeurIPS，2023–2026 年共 781 篇。