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 136 篇，第 3 / 3 页

101. ICML 2025RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
102. ICML 2025SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning
103. ICML 2025SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
104. ICML 2025Self-Bootstrapping for Versatile Test-Time Adaptation
105. ICML 2025Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptation
106. ICML 2025SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
107. ICML 2025SLiM: One-shot Quantization and Sparsity with Low-rank Approximation for LLM Weight Compression
108. ICML 2025SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
109. ICML 2025Sparse Autoencoders, Again?
110. ICML 2025Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
111. ICML 2025SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity
112. ICML 2025Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
113. ICML 2025Surrogate Prompt Learning: Towards Efficient and Diverse Prompt Learning for Vision-Language Models
114. ICML 2025SynEVO: A neuro-inspired spatiotemporal evolutional framework for cross-domain adaptation
115. ICML 2025Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
116. ICML 2025Targeted Low-rank Refinement: Enhancing Sparse Language Models with Precision
117. ICML 2025Tensorized Multi-View Multi-Label Classification via Laplace Tensor Rank
118. ICML 2025Test-Time Learning for Large Language Models
119. ICML 2025Test-Time Selective Adaptation for Uni-Modal Distribution Shift in Multi-Modal Data
120. ICML 2025Text-to-LoRA: Instant Transformer Adaption
121. ICML 2025The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
122. ICML 2025The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport
123. ICML 2025Theoretical Performance Guarantees for Partial Domain Adaptation via Partial Optimal Transport
124. ICML 2025TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
125. ICML 2025Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
126. ICML 2025Tracking Most Significant Shifts in Infinite-Armed Bandits
127. ICML 2025Transfer Q-Learning with Composite MDP Structures
128. ICML 2025TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree
129. ICML 2025Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization
130. ICML 2025Ultra-Resolution Adaptation with Ease
131. ICML 2025Unified K-Means Clustering with Label-Guided Manifold Learning
132. ICML 2025Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting
133. ICML 2025Vision Graph Prompting via Semantic Low-Rank Decomposition
134. ICML 2025Vision-Language Model Selection and Reuse for Downstream Adaptation
135. ICML 2025WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models
136. ICML 2025Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models

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。