Low-Rank Adaptation papers, 2023–2026

Key findings

• Low-Rank Adaptation went from 282 papers in 2023 to 841 in 2026, roughly 3.0x in three years.
• NeurIPS publishes the most Low-Rank Adaptation work: 781 papers from 2023 to 2026, 34% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 4 in 2023 to 61 in 2026.
• Among the 5 topics under Optimization and Scaling, it ranks #1 by 2026 paper count; the fastest grower in the group, Scaling Laws, is up 4.1x versus 3.0x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Low-Rank Adaptation papers

152 papers, page 3 of 4

101. ICLR 2025Perplexity Trap: PLM-Based Retrievers Overrate Low Perplexity Documents
102. ICLR 2025pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation
103. ICLR 2025PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches
104. ICLR 2025Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
105. ICLR 2025Proxy Denoising for Source-Free Domain Adaptation
106. ICLR 2025QERA: an Analytical Framework for Quantization Error Reconstruction
107. ICLR 2025Quantum-PEFT: Ultra parameter-efficient fine-tuning
108. ICLR 2025R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference
109. ICLR 2025RandLoRA: Full rank parameter-efficient fine-tuning of large models
110. ICLR 2025RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
111. ICLR 2025RaSA: Rank-Sharing Low-Rank Adaptation
112. ICLR 2025Re-Imagining Multimodal Instruction Tuning: A Representation View
113. ICLR 2025RECAST: Reparameterized, Compact weight Adaptation for Sequential Tasks
114. ICLR 2025Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA
115. ICLR 2025Revisiting Prefix-tuning: Statistical Benefits of Reparameterization among Prompts
116. ICLR 2025SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation
117. ICLR 2025SaRA: High-Efficient Diffusion Model Fine-tuning with Progressive Sparse Low-Rank Adaptation
118. ICLR 2025Scalable Decentralized Learning with Teleportation
119. ICLR 2025Scaling Transformers for Low-Bitrate High-Quality Speech Coding
120. ICLR 2025SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning
121. ICLR 2025SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection
122. ICLR 2025Selective Aggregation for Low-Rank Adaptation in Federated Learning
123. ICLR 2025Semi-Supervised CLIP Adaptation by Enforcing Semantic and Trapezoidal Consistency
124. ICLR 2025SEPARATE: A Simple Low-rank Projection for Gradient Compression in Modern Large-scale Model Training Process
125. ICLR 2025Shallow diffusion networks provably learn hidden low-dimensional structure
126. ICLR 2025Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions
127. ICLR 2025Skill Expansion and Composition in Parameter Space
128. ICLR 2025SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs
129. ICLR 2025Smoothing the Shift: Towards Stable Test-Time Adaptation under Complex Multimodal Noises
130. ICLR 2025SMT: Fine-Tuning Large Language Models with Sparse Matrices
131. ICLR 2025SPDIM: Source-Free Unsupervised Conditional and Label Shift Adaptation in EEG
132. ICLR 2025SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning
133. ICLR 2025Surprising Effectiveness of pretraining Ternary Language Model at Scale
134. ICLR 2025SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models
135. ICLR 2025TabM: Advancing tabular deep learning with parameter-efficient ensembling
136. ICLR 2025Test-Time Adaptation for Combating Missing Modalities in Egocentric Videos
137. ICLR 2025Test-Time Ensemble via Linear Mode Connectivity: A Path to Better Adaptation
138. ICLR 2025The Unreasonable Ineffectiveness of the Deeper Layers
139. ICLR 2025Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs
140. ICLR 2025Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization
141. ICLR 2025Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
142. ICLR 2025Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
143. ICLR 2025Transformers Learn Low Sensitivity Functions: Investigations and Implications
144. ICLR 2025TTVD: Towards a Geometric Framework for Test-Time Adaptation Based on Voronoi Diagram
145. ICLR 2025Tuning Frequency Bias of State Space Models
146. ICLR 2025Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization
147. ICLR 2025u-$\mu$P: The Unit-Scaled Maximal Update Parametrization
148. ICLR 2025Unified Parameter-Efficient Unlearning for LLMs
149. ICLR 2025Unleashing the Power of Task-Specific Directions in Parameter Efficient Fine-tuning
150. ICLR 2025Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning

FAQ

How many Low-Rank Adaptation papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,273 in total: 282 in 2023, 518 in 2024, 632 in 2025, 841 in 2026.

How many Low-Rank Adaptation papers are at NeurIPS 2026?

NeurIPS 2026 has 269 Low-Rank Adaptation papers, versus 241 the year before.

How many Low-Rank Adaptation papers are at ICLR 2026?

ICLR 2026 has 184 Low-Rank Adaptation papers, versus 152 the year before.

How many Low-Rank Adaptation papers are at ICML 2026?

ICML 2026 has 240 Low-Rank Adaptation papers, versus 136 the year before.

How many Low-Rank Adaptation papers are at CVPR 2026?

CVPR 2026 has 148 Low-Rank Adaptation papers, versus 103 the year before.

Which conference publishes the most Low-Rank Adaptation papers?

NeurIPS, with 781 papers from 2023 to 2026.