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

136 papers, page 2 of 3

51. ICML 2025HiRemate: Hierarchical Approach for Efficient Re-materialization of Neural Networks
52. ICML 2025Homophily Enhanced Graph Domain Adaptation
53. ICML 2025Hyper-Transforming Latent Diffusion Models
54. ICML 2025In-Context Adaptation to Concept Drift for Learned Database Operations
55. ICML 2025InfoSAM: Fine-Tuning the Segment Anything Model from An Information-Theoretic Perspective
56. ICML 2025IntLoRA: Integral Low-rank Adaptation of Quantized Diffusion Models
57. ICML 2025Joint Localization and Activation Editing for Low-Resource Fine-Tuning
58. ICML 2025L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning
59. ICML 2025Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
60. ICML 2025LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
61. ICML 2025Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees
62. ICML 2025Learning to Reuse Policies in State Evolvable Environments
63. ICML 2025LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning
64. ICML 2025Liger: Linearizing Large Language Models to Gated Recurrent Structures
65. ICML 2025Linear Mode Connectivity between Multiple Models modulo Permutation Symmetries
66. ICML 2025LoRA Training Provably Converges to a Low-Rank Global Minimum Or It Fails Loudly (But it Probably Won't Fail)
67. ICML 2025LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
68. ICML 2025Low-Dimension-to-High-Dimension Generalization and Its Implications for Length Generalization
69. ICML 2025Low-distortion and GPU-compatible Tree Embeddings in Hyperbolic Space
70. ICML 2025Low-Rank Adapting Models for Sparse Autoencoders
71. ICML 2025Low-Rank Tensor Transitions (LoRT) for Transferable Tensor Regression
72. ICML 2025Low-Rank Thinning
73. ICML 2025LowRA: Accurate and Efficient LoRA Fine-Tuning of LLMs under 2 Bits
74. ICML 2025LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
75. ICML 2025Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment
76. ICML 2025Meta-Reinforcement Learning with Adaptation from Human Feedback via Preference-Order-Preserving Task Embedding
77. ICML 2025MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters
78. ICML 2025Mind the Gap: a Spectral Analysis of Rank Collapse and Signal Propagation in Attention Layers
79. ICML 2025Mixture of Lookup Experts
80. ICML 2025Model Swarms: Collaborative Search to Adapt LLM Experts via Swarm Intelligence
81. ICML 2025MoE-SVD: Structured Mixture-of-Experts LLMs Compression via Singular Value Decomposition
82. ICML 2025Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning
83. ICML 2025MoRAgent: Parameter Efficient Agent Tuning with Mixture-of-Roles
84. ICML 2025Neutral residues: revisiting adapters for model extension
85. ICML 2025Olica: Efficient Structured Pruning of Large Language Models without Retraining
86. ICML 2025Optimizing Large Language Model Training Using FP4 Quantization
87. ICML 2025Oscillation-Reduced MXFP4 Training for Vision Transformers
88. ICML 2025Parameter-Efficient Fine-Tuning of State Space Models
89. ICML 2025Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models
90. ICML 2025Preconditioned Riemannian Gradient Descent Algorithm for Low-Multilinear-Rank Tensor Completion
91. ICML 2025Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves
92. ICML 2025Projection Pursuit Density Ratio Estimation
93. ICML 2025Provable and Practical Online Learning Rate Adaptation with Hypergradient Descent
94. ICML 2025PTTA: Purifying Malicious Samples for Test-Time Model Adaptation
95. ICML 2025Rank-One Modified Value Iteration
96. ICML 2025Ranked Entropy Minimization for Continual Test-Time Adaptation
97. ICML 2025Ranking with Multiple Oracles: From Weak to Strong Stochastic Transitivity
98. ICML 2025RepLoRA: Reparameterizing Low-rank Adaptation via the Perspective of Mixture of Experts
99. ICML 2025ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals
100. ICML 2025Robust Sparsification via Sensitivity

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.