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 27 of 46

1301. NeurIPS 2025FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic
1302. NeurIPS 2025Fantastic Features and Where to Find Them: A Probing Method to combine Features from Multiple Foundation Models
1303. NeurIPS 2025Fast Last-Iterate Convergence of SGD in the Smooth Interpolation Regime
1304. NeurIPS 2025FedSVD: Adaptive Orthogonalization for Private Federated Learning with LoRA
1305. NeurIPS 2025Finding Low-Rank Matrix Weights in DNNs via Riemannian Optimization: RAdaGrad and RAdamW
1306. NeurIPS 2025Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
1307. NeurIPS 2025FlashBias: Fast Computation of Attention with Bias
1308. NeurIPS 2025FlyLoRA: Boosting Task Decoupling and Parameter Efficiency via Implicit Rank-Wise Mixture-of-Experts
1309. NeurIPS 2025FocalCodec: Low-Bitrate Speech Coding via Focal Modulation Networks
1310. NeurIPS 2025FOCUS: Internal MLLM Representations for Efficient Fine-Grained Visual Question Answering
1311. NeurIPS 2025FP4 All the Way: Fully Quantized Training of Large Language Models
1312. NeurIPS 2025From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics
1313. NeurIPS 2025Functional Complexity-adaptive Temporal Tensor Decomposition
1314. NeurIPS 2025GaRA-SAM: Robustifying Segment Anything Model with Gated-Rank Adaptation
1315. NeurIPS 2025Gated Integration of Low-Rank Adaptation for Continual Learning of Large Language Models
1316. NeurIPS 2025GeGS-PCR: Fast and Robust Color 3D Point Cloud Registration with Two-Stage Geometric-3DGS Fusion
1317. NeurIPS 2025Generalization Bounds for Rank-sparse Neural Networks
1318. NeurIPS 2025GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters
1319. NeurIPS 2025Geometry-Aware Collaborative Multi-Solutions Optimizer for Model Fine-Tuning with Parameter Efficiency
1320. NeurIPS 2025GoRA: Gradient-driven Adaptive Low Rank Adaptation
1321. NeurIPS 2025GraLoRA: Granular Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
1322. NeurIPS 2025Graph Data Selection for Domain Adaptation: A Model-Free Approach
1323. NeurIPS 2025Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
1324. NeurIPS 2025Hawaii: Hierarchical Visual Knowledge Transfer for Efficient Vision-Language Models
1325. NeurIPS 2025HeavyWater and SimplexWater: Distortion-free LLM Watermarks for Low-Entropy Distributions
1326. NeurIPS 2025HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
1327. NeurIPS 2025Heterogeneous Diffusion Structure Inference for Network Cascade
1328. NeurIPS 2025Hierachical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
1329. NeurIPS 2025Hierarchical Optimization via LLM-Guided Objective Evolution for Mobility-on-Demand Systems
1330. NeurIPS 2025High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model
1331. NeurIPS 2025HiMoLE: Towards OOD-Robust LoRA via Hierarchical Mixture of Experts
1332. NeurIPS 2025How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
1333. NeurIPS 2025Hybrid Re-matching for Continual Learning with Parameter-Efficient Tuning
1334. NeurIPS 2025Hyperbolic Fine-Tuning for Large Language Models
1335. NeurIPS 2025Identifiability of Deep Polynomial Neural Networks
1336. NeurIPS 2025Interpretable and Parameter Efficient Graph Neural Additive Models with Random Fourier Features
1337. NeurIPS 2025Irrational Complex Rotations Empower Low-bit Optimizers
1338. NeurIPS 2025Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable Refinement
1339. NeurIPS 2025Latent Space Factorization in LoRA
1340. NeurIPS 2025LaX: Boosting Low-Rank Training of Foundation Models via Latent Crossing
1341. NeurIPS 2025Learning Counterfactual Outcomes Under Rank Preservation
1342. NeurIPS 2025Learning Grouped Lattice Vector Quantizers for Low-Bit LLM Compression
1343. NeurIPS 2025Learning Relative Gene Expression Trends from Pathology Images in Spatial Transcriptomics
1344. NeurIPS 2025Learning Source-Free Domain Adaptation for Visible-Infrared Person Re-Identification
1345. NeurIPS 2025Learning to Rank for In-Context Example Retrieval
1346. NeurIPS 2025Lifelong Test-Time Adaptation via Online Learning in Tracked Low-Dimensional Subspace
1347. NeurIPS 2025Linear Transformers Implicitly Discover Unified Numerical Algorithms
1348. NeurIPS 2025Linearization Explains Fine-Tuning in Large Language Models
1349. NeurIPS 2025LittleBit: Ultra Low-Bit Quantization via Latent Factorization
1350. NeurIPS 2025LLM at Network Edge: A Layer-wise Efficient Federated Fine-tuning Approach

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.