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 37 of 46

1801. NeurIPS 2024A Bayesian Approach to Data Point Selection
1802. NeurIPS 2024A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
1803. NeurIPS 2024A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
1804. NeurIPS 2024Abrupt Learning in Transformers: A Case Study on Matrix Completion
1805. NeurIPS 2024Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
1806. NeurIPS 2024An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
1807. NeurIPS 2024AUC Maximization under Positive Distribution Shift
1808. NeurIPS 2024BAdam: A Memory Efficient Full Parameter Optimization Method for Large Language Models
1809. NeurIPS 2024Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models
1810. NeurIPS 2024BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text
1811. NeurIPS 2024Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback
1812. NeurIPS 2024BitsFusion: 1.99 bits Weight Quantization of Diffusion Model
1813. NeurIPS 2024BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference
1814. NeurIPS 2024BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
1815. NeurIPS 2024BOLD: Boolean Logic Deep Learning
1816. NeurIPS 2024Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension
1817. NeurIPS 2024Bridging The Gap between Low-rank and Orthogonal Adaptation via Householder Reflection Adaptation
1818. NeurIPS 2024Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers
1819. NeurIPS 2024Cherry on Top: Parameter Heterogeneity and Quantization in Large Language Models
1820. NeurIPS 2024Coherence-free Entrywise Estimation of Eigenvectors in Low-rank Signal-plus-noise Matrix Models
1821. NeurIPS 2024CoMERA: Computing- and Memory-Efficient Training via Rank-Adaptive Tensor Optimization
1822. NeurIPS 2024Communication Efficient Distributed Training with Distributed Lion
1823. NeurIPS 2024Compressing Large Language Models using Low Rank and Low Precision Decomposition
1824. NeurIPS 2024Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
1825. NeurIPS 2024Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
1826. NeurIPS 2024CorDA: Context-Oriented Decomposition Adaptation of Large Language Models for Task-Aware Parameter-Efficient Fine-tuning
1827. NeurIPS 2024Data-Efficient Learning with Neural Programs
1828. NeurIPS 2024Decomposed Prompt Decision Transformer for Efficient Unseen Task Generalization
1829. NeurIPS 2024DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform
1830. NeurIPS 2024Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models
1831. NeurIPS 2024Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models
1832. NeurIPS 2024Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
1833. NeurIPS 2024Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation
1834. NeurIPS 2024DoFIT: Domain-aware Federated Instruction Tuning with Alleviated Catastrophic Forgetting
1835. NeurIPS 2024DOPPLER: Differentially Private Optimizers with Low-pass Filter for Privacy Noise Reduction
1836. NeurIPS 2024DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
1837. NeurIPS 2024Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation
1838. NeurIPS 2024EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding
1839. NeurIPS 2024Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
1840. NeurIPS 2024Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games
1841. NeurIPS 2024Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
1842. NeurIPS 2024Efficient Discrepancy Testing for Learning with Distribution Shift
1843. NeurIPS 2024Efficient Lifelong Model Evaluation in an Era of Rapid Progress
1844. NeurIPS 2024Efficient LLM Scheduling by Learning to Rank
1845. NeurIPS 2024Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
1846. NeurIPS 2024Efficient Reinforcement Learning by Discovering Neural Pathways
1847. NeurIPS 2024EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography
1848. NeurIPS 2024Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
1849. NeurIPS 2024Entrywise error bounds for low-rank approximations of kernel matrices
1850. NeurIPS 2024Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems

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.