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 8 of 12

351. ICML 2025SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity
352. ICML 2025Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
353. ICML 2025Surrogate Prompt Learning: Towards Efficient and Diverse Prompt Learning for Vision-Language Models
354. ICML 2025SynEVO: A neuro-inspired spatiotemporal evolutional framework for cross-domain adaptation
355. ICML 2025Tackling Dimensional Collapse toward Comprehensive Universal Domain Adaptation
356. ICML 2025Targeted Low-rank Refinement: Enhancing Sparse Language Models with Precision
357. ICML 2025Tensorized Multi-View Multi-Label Classification via Laplace Tensor Rank
358. ICML 2025Test-Time Learning for Large Language Models
359. ICML 2025Test-Time Selective Adaptation for Uni-Modal Distribution Shift in Multi-Modal Data
360. ICML 2025Text-to-LoRA: Instant Transformer Adaption
361. ICML 2025The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
362. ICML 2025The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport
363. ICML 2025Theoretical Performance Guarantees for Partial Domain Adaptation via Partial Optimal Transport
364. ICML 2025TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
365. ICML 2025Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
366. ICML 2025Tracking Most Significant Shifts in Infinite-Armed Bandits
367. ICML 2025Transfer Q-Learning with Composite MDP Structures
368. ICML 2025TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree
369. ICML 2025Tuning Sequential Monte Carlo Samplers via Greedy Incremental Divergence Minimization
370. ICML 2025Ultra-Resolution Adaptation with Ease
371. ICML 2025Unified K-Means Clustering with Label-Guided Manifold Learning
372. ICML 2025Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting
373. ICML 2025Vision Graph Prompting via Semantic Low-Rank Decomposition
374. ICML 2025Vision-Language Model Selection and Reuse for Downstream Adaptation
375. ICML 2025WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models
376. ICML 2025Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models
377. ICML 20243D Geometric Shape Assembly via Efficient Point Cloud Matching
378. ICML 2024A Closer Look at the Limitations of Instruction Tuning
379. ICML 2024A Tensor Decomposition Perspective on Second-order RNNs
380. ICML 2024Adaptively Learning to Select-Rank in Online Platforms
381. ICML 2024Allocation Requires Prediction Only if Inequality Is Low
382. ICML 2024AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training
383. ICML 2024Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs
384. ICML 2024APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
385. ICML 2024AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
386. ICML 2024Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
387. ICML 2024Asymmetry in Low-Rank Adapters of Foundation Models
388. ICML 2024Batch Singular Value Polarization and Weighted Semantic Augmentation for Universal Domain Adaptation
389. ICML 2024Bayesian Adaptation of Network Depth and Width for Continual Learning
390. ICML 2024BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
391. ICML 2024Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
392. ICML 2024Category-Aware Active Domain Adaptation
393. ICML 2024CauDiTS: Causal Disentangled Domain Adaptation of Multivariate Time Series
394. ICML 2024Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
395. ICML 2024Collage: Light-Weight Low-Precision Strategy for LLM Training
396. ICML 2024CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
397. ICML 2024Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
398. ICML 2024Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
399. ICML 2024Cross-Domain Policy Adaptation by Capturing Representation Mismatch
400. ICML 2024Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes

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.