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

2,272 papers, page 43 of 46

2101. ICLR 2023MECTA: Memory-Economic Continual Test-Time Model Adaptation
2102. ICLR 2023Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform
2103. ICLR 2023Moving Forward by Moving Backward: Embedding Action Impact over Action Semantics
2104. ICLR 2023Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
2105. ICLR 2023Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
2106. ICLR 2023Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
2107. ICLR 2023Online Low Rank Matrix Completion
2108. ICLR 2023Parameter-Efficient Fine-Tuning Design Spaces
2109. ICLR 2023Parametrizing Product Shape Manifolds by Composite Networks
2110. ICLR 2023Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms
2111. ICLR 2023Provably Auditing Ordinary Least Squares in Low Dimensions
2112. ICLR 2023Quantifying Memorization Across Neural Language Models
2113. ICLR 2023Representation Learning for Low-rank General-sum Markov Games
2114. ICLR 2023Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks
2115. ICLR 2023Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
2116. ICLR 2023Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
2117. ICLR 2023SCoMoE: Efficient Mixtures of Experts with Structured Communication
2118. ICLR 2023Self-Distillation for Further Pre-training of Transformers
2119. ICLR 2023Sparse Random Networks for Communication-Efficient Federated Learning
2120. ICLR 2023Spatio-temporal point processes with deep non-stationary kernels
2121. ICLR 2023Spikformer: When Spiking Neural Network Meets Transformer
2122. ICLR 2023Surgical Fine-Tuning Improves Adaptation to Distribution Shifts
2123. ICLR 2023Tensor-Based Sketching Method for the Low-Rank Approximation of Data Streams.
2124. ICLR 2023Towards a Unified Theoretical Understanding of Non-contrastive Learning via Rank Differential Mechanism
2125. ICLR 2023Towards Stable Test-time Adaptation in Dynamic Wild World
2126. ICLR 2023Treeformer: Dense Gradient Trees for Efficient Attention Computation
2127. ICLR 2023Tuning Frequency Bias in Neural Network Training with Nonuniform Data
2128. ICLR 2023UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining
2129. ICLR 2023When Source-Free Domain Adaptation Meets Learning with Noisy Labels
2130. ICML 2023A Three-regime Model of Network Pruning
2131. ICML 2023Adversarial Parameter Attack on Deep Neural Networks
2132. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
2133. ICML 2023Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions
2134. ICML 2023Bootstrap in High Dimension with Low Computation
2135. ICML 2023Conditional Tree Matching for Inference-Time Adaptation of Tree Prediction Models
2136. ICML 2023Curious Replay for Model-based Adaptation
2137. ICML 2023Data Efficient Neural Scaling Law via Model Reusing
2138. ICML 2023Diffusion Models are Minimax Optimal Distribution Estimators
2139. ICML 2023Discover-Then-Rank Unlabeled Support Vectors in the Dual Space for Multi-Class Active Learning
2140. ICML 2023DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule
2141. ICML 2023Domain Adaptation for Time Series Under Feature and Label Shifts
2142. ICML 2023Double-Weighting for Covariate Shift Adaptation
2143. ICML 2023Efficient List-Decodable Regression using Batches
2144. ICML 2023Efficient Personalized Federated Learning via Sparse Model-Adaptation
2145. ICML 2023ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models
2146. ICML 2023Exploring the Benefits of Training Expert Language Models over Instruction Tuning
2147. ICML 2023Fast $(1+\varepsilon)$-Approximation Algorithms for Binary Matrix Factorization
2148. ICML 2023Flash: Concept Drift Adaptation in Federated Learning
2149. ICML 2023Generalized Reductions: Making any Hierarchical Clustering Fair and Balanced with Low Cost
2150. ICML 2023Geometric Autoencoders - What You See is What You Decode

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.