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

840 papers, page 10 of 17

451. ICML 2026Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective
452. ICML 2026Midtraining Bridges Pretraining and Posttraining Distributions
453. ICML 2026Mining Useful General Data for Low-Resource Domain Adaptation
454. ICML 2026Mitigating Error Propagation in Low-Rank Approximation of Large Models via Distribution-Aware Whitening
455. ICML 2026ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World
456. ICML 2026MODEL SOUPS NEED ONLY ONE INGREDIENT
457. ICML 2026Multi-Label Test-Time Adaptation with Bayesian Conditional Priors
458. ICML 2026MultiLoReFT: Decoupling Shared and Modality-Specific Subspaces in Multimodal Learning via Low-Rank Representation Fine-Tuning
459. ICML 2026Multiple Choice Learning of Low-Rank Adapters for Language Modeling
460. ICML 2026NanoQuant: Efficient Sub-1-Bit Quantization of Large Language Models
461. ICML 2026NaRA: Noise-Aware LoRA for Parameter-Efficient Fine-Tuning of Diffusion LLMs
462. ICML 2026NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs
463. ICML 2026Neural Low-Discrepancy Sequences
464. ICML 2026Neural-HSS: Hierarchical Semi-Separable Neural PDE Solver
465. ICML 2026Noise-Guided Transport: Imitation Learning from Random Priors
466. ICML 2026Nonconvex Low-Rank Tensor Representation with Deep Priors for Multiview Subspace Clustering
467. ICML 2026Obliviate: Efficient Unlearning in Recommender Systems
468. ICML 2026On the Convergence Rate of LoRA Gradient Descent
469. ICML 2026On the Effect of Misspecifying the Embedding Dimension in Low-rank Network Models
470. ICML 2026On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
471. ICML 2026On the Theoretical Limitations of Embedding-based Link Prediction
472. ICML 2026Online Change Point Detection for Multivariate Inhomogeneous Poisson Processes Time Series
473. ICML 2026Operationalising the Superficial Alignment Hypothesis via Task Complexity
474. ICML 2026Optimizing Rank for High-Fidelity Implicit Neural Representations
475. ICML 2026OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization
476. ICML 2026Overcoming PINNs Failure Modes In High Dimension With Low-Rank Fourier Sum
477. ICML 2026OVLR: Efficient, Scalable, and Robust Training via Output-Level Variance-Reduced Likelihood Ratio
478. ICML 2026Parameters as Experts: Adapting Vision Models with Dynamic Parameter Routing
479. ICML 2026PLATE: Plasticity-Tunable Efficient Adapters for Geometry-Aware Continual Learning
480. ICML 2026PLoRA: Efficient Concurrent LoRA Training for Large Language Models
481. ICML 2026PRAC: Principal-Random Subspace for LLM Activation Compression and Memory-Efficient Training
482. ICML 2026Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates
483. ICML 2026Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
484. ICML 2026PRISM: Gauge-Invariant Tangent-Space Differentially Private LoRA
485. ICML 2026Private and Stable Test-time Adaptation with Differential Privacy
486. ICML 2026Probability-Entropy Calibration: An Elastic Indicator for Adaptive Fine-tuning
487. ICML 2026Progressive Graph Structure Adjustment for Homophily Shift Adaptation
488. ICML 2026ProjQ: Project-and-Quantize for Adapter-Aware LLM Compression
489. ICML 2026Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function
490. ICML 2026Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles
491. ICML 2026RaBiT: Residual Aware Binarization Training for Accurate and Efficient LLMs
492. ICML 2026Rank-Aware Spectral Bounds on Attention Logits for Stable Low-Precision Training
493. ICML 2026Rank-Learner: Orthogonal Ranking of Treatment Effects
494. ICML 2026Rational Neural Networks have Expressivity Advantages
495. ICML 2026Reference-Free Meta-Learning for Generalized Implicit Neural Representation in Efficient MRI Reconstruction
496. ICML 2026Refining Dual Spectral Sparsity in Transformed Tensor Singular Values
497. ICML 2026Representation Drift Compensation: A Near-Zero Inference Cost Enhancement for LLM Decomposition
498. ICML 2026Rethinking Low-Confidence Pseudo Labels: Influence-Aware Semi-Supervised Fine-Tuning for Hyperspectral Change Detection
499. ICML 2026Rethinking Parameter Sharing as Graph Coloring for Structured Compression
500. ICML 2026Rethinking the Flow-based Gradual Domain Adaptation: A Semi-Dual Optimal Transport Perspective

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.