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

781 papers, page 7 of 16

301. NeurIPS 2025Composing Linear Layers from Irreducibles
302. NeurIPS 2025Compress to Impress: Efficient LLM Adaptation Using a Single Gradient Step on 100 Samples
303. NeurIPS 2025Continual Knowledge Adaptation for Reinforcement Learning
304. NeurIPS 2025Controlled Visual Hallucination via Thalamus-Driven Decoupling Network for Domain Adaptation of Black-Box Predictors
305. NeurIPS 2025Correlated Low-Rank Adaptation for ConvNets
306. NeurIPS 2025CrossSpectra: Exploiting Cross-Layer Smoothness for Parameter-Efficient Fine-Tuning
307. NeurIPS 2025Curvature Tuning: Provable Training-free Model Steering From a Single Parameter
308. NeurIPS 2025D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction
309. NeurIPS 2025Data Efficient Adaptation in Large Language Models via Continuous Low-Rank Fine-Tuning
310. NeurIPS 2025DEFT: Decompositional Efficient Fine-Tuning for Text-to-Image Models
311. NeurIPS 2025DeltaProduct: Improving State-Tracking in Linear RNNs via Householder Products
312. NeurIPS 2025Demystifying Language Model Forgetting with Low-rank Example Associations
313. NeurIPS 2025Dependency Parsing is More Parameter-Efficient with Normalization
314. NeurIPS 2025Differentially Private Federated Low Rank Adaptation Beyond Fixed-Matrix
315. NeurIPS 2025Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation
316. NeurIPS 2025Disentangling misreporting from genuine adaptation in strategic settings: a causal approach
317. NeurIPS 2025Distribution-Aligned Decoding for Efficient LLM Task Adaptation
318. NeurIPS 2025Distribution-Aware Tensor Decomposition for Compression of Convolutional Neural Networks
319. NeurIPS 2025DP-LLM: Runtime Model Adaptation with Dynamic Layer-wise Precision Assignment
320. NeurIPS 2025Dr. RAW: Towards General High-Level Vision from RAW with Efficient Task Conditioning
321. NeurIPS 2025Drag-and-Drop LLMs: Zero-Shot Prompt-to-Weights
322. NeurIPS 2025Dual Prototype-Enhanced Contrastive Framework for Class-Imbalanced Graph Domain Adaptation
323. NeurIPS 2025DUO: No Compromise to Accuracy Degradation
324. NeurIPS 2025Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
325. NeurIPS 2025ECO: Evolving Core Knowledge for Efficient Transfer
326. NeurIPS 2025Efficient $k$-Sparse Band–Limited Interpolation with Improved Approximation Ratio
327. NeurIPS 2025Efficient Data Selection at Scale via Influence Distillation
328. NeurIPS 2025Efficient Large Language Model Inference with Neural Block Linearization
329. NeurIPS 2025Efficient Last-Iterate Convergence in Solving Extensive-Form Games
330. NeurIPS 2025Efficient Low Rank Attention for Long-Context Inference in Large Language Models
331. NeurIPS 2025Efficient Parametric SVD of Koopman Operator for Stochastic Dynamical Systems
332. NeurIPS 2025Efficient Safe Meta-Reinforcement Learning: Provable Near-Optimality and Anytime Safety
333. NeurIPS 2025Efficient Training of Minimal and Maximal Low-Rank Recurrent Neural Networks
334. NeurIPS 2025EMLoC: Emulator-based Memory-efficient Fine-tuning with LoRA Correction
335. NeurIPS 2025Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training
336. NeurIPS 2025Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
337. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
338. NeurIPS 2025F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
339. NeurIPS 2025FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
340. NeurIPS 2025Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models
341. NeurIPS 2025Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
342. NeurIPS 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
343. NeurIPS 2025Finding Low-Rank Matrix Weights in DNNs via Riemannian Optimization: RAdaGrad and RAdamW
344. NeurIPS 2025Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
345. NeurIPS 2025FlashBias: Fast Computation of Attention with Bias
346. NeurIPS 2025FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
347. NeurIPS 2025FocalCodec: Low-Bitrate Speech Coding via Focal Modulation Networks
348. NeurIPS 2025FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering
349. NeurIPS 2025FP4 All the Way: Fully Quantized Training of Large Language Models
350. NeurIPS 2025From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics

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.