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

518 papers, page 8 of 11

351. NeurIPS 2024Compressing Large Language Models using Low Rank and Low Precision Decomposition
352. NeurIPS 2024Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
353. NeurIPS 2024Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
354. NeurIPS 2024CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning
355. NeurIPS 2024Data-Efficient Learning with Neural Programs
356. NeurIPS 2024Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization
357. NeurIPS 2024DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform
358. NeurIPS 2024Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models
359. NeurIPS 2024Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models
360. NeurIPS 2024Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
361. NeurIPS 2024Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation
362. NeurIPS 2024DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting
363. NeurIPS 2024DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction
364. NeurIPS 2024DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
365. NeurIPS 2024Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation
366. NeurIPS 2024EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding
367. NeurIPS 2024Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
368. NeurIPS 2024Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games
369. NeurIPS 2024Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
370. NeurIPS 2024Efficient Discrepancy Testing for Learning with Distribution Shift
371. NeurIPS 2024Efficient Lifelong Model Evaluation in an Era of Rapid Progress
372. NeurIPS 2024Efficient LLM Scheduling by Learning to Rank
373. NeurIPS 2024Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
374. NeurIPS 2024Efficient Reinforcement Learning by Discovering Neural Pathways
375. NeurIPS 2024EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography
376. NeurIPS 2024Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
377. NeurIPS 2024Entrywise error bounds for low-rank approximations of kernel matrices
378. NeurIPS 2024Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
379. NeurIPS 2024Expanding Sparse Tuning for Low Memory Usage
380. NeurIPS 2024Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing
381. NeurIPS 2024F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning
382. NeurIPS 2024Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
383. NeurIPS 2024Federated Black-Box Adaptation for Semantic Segmentation
384. NeurIPS 2024Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
385. NeurIPS 2024Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
386. NeurIPS 2024Fit for our purpose, not yours: Benchmark for a low-resource, Indigenous language
387. NeurIPS 2024FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
388. NeurIPS 2024FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
389. NeurIPS 2024FouRA: Fourier Low-Rank Adaptation
390. NeurIPS 2024From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement
391. NeurIPS 2024Frustratingly Easy Test-Time Adaptation of Vision-Language Models
392. NeurIPS 2024Geometry-aware training of factorized layers in tensor Tucker format
393. NeurIPS 2024Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
394. NeurIPS 2024Group and Shuffle: Efficient Structured Orthogonal Parametrization
395. NeurIPS 2024Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
396. NeurIPS 2024Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
397. NeurIPS 2024How do Large Language Models Handle Multilingualism?
398. NeurIPS 2024HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
399. NeurIPS 2024Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
400. NeurIPS 2024Improving Deep Learning Optimization through Constrained Parameter Regularization

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.