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

565 papers, page 10 of 12

451. ICML 2024LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
452. ICML 2024LoRA Training in the NTK Regime has No Spurious Local Minima
453. ICML 2024LoRA+: Efficient Low Rank Adaptation of Large Models
454. ICML 2024Low-Cost High-Power Membership Inference Attacks
455. ICML 2024Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
456. ICML 2024Low-Rank Similarity Mining for Multimodal Dataset Distillation
457. ICML 2024LQER: Low-Rank Quantization Error Reconstruction for LLMs
458. ICML 2024Maestro: Uncovering Low-Rank Structures via Trainable Decomposition
459. ICML 2024On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
460. ICML 2024On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors
461. ICML 2024Online Matrix Completion: A Collaborative Approach with Hott Items
462. ICML 2024Operator SVD with Neural Networks via Nested Low-Rank Approximation
463. ICML 2024Optimal Coresets for Low-Dimensional Geometric Median
464. ICML 2024Pairwise Alignment Improves Graph Domain Adaptation
465. ICML 2024Parallel Affine Transformation Tuning of Markov Chain Monte Carlo
466. ICML 2024Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
467. ICML 2024Parameter Estimation in DAGs from Incomplete Data via Optimal Transport
468. ICML 2024Parameter-Efficient Fine-Tuning with Controls
469. ICML 2024Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
470. ICML 2024PcLast: Discovering Plannable Continuous Latent States
471. ICML 2024Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
472. ICML 2024Prodigy: An Expeditiously Adaptive Parameter-Free Learner
473. ICML 2024Prompt-tuning Latent Diffusion Models for Inverse Problems
474. ICML 2024Provable Interactive Learning with Hindsight Instruction Feedback
475. ICML 2024Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation
476. ICML 2024Random features models: a way to study the success of naive imputation
477. ICML 2024Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
478. ICML 2024Recovering the Pre-Fine-Tuning Weights of Generative Models
479. ICML 2024Reducing Fine-Tuning Memory Overhead by Approximate and Memory-Sharing Backpropagation
480. ICML 2024Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
481. ICML 2024Reweighted Solutions for Weighted Low Rank Approximation
482. ICML 2024Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
483. ICML 2024RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
484. ICML 2024Sample-Efficient Multiagent Reinforcement Learning with Reset Replay
485. ICML 2024Self-attention Networks Localize When QK-eigenspectrum Concentrates
486. ICML 2024SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets
487. ICML 2024SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic
488. ICML 2024Sign Rank Limitations for Inner Product Graph Decoders
489. ICML 2024Simplicity Bias via Global Convergence of Sharpness Minimization
490. ICML 2024Sparse is Enough in Fine-tuning Pre-trained Large Language Models
491. ICML 2024SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
492. ICML 2024SuDA: Support-based Domain Adaptation for Sim2Real Hinge Joint Tracking with Flexible Sensors
493. ICML 2024Symmetric Matrix Completion with ReLU Sampling
494. ICML 2024TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules
495. ICML 2024Testing the Feasibility of Linear Programs with Bandit Feedback
496. ICML 2024Towards efficient deep spiking neural networks construction with spiking activity based pruning
497. ICML 2024Trainable Transformer in Transformer
498. ICML 2024Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms
499. ICML 2024Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
500. ICML 2024Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning

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.