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

781 papers, page 16 of 16

751. NeurIPS 2023PDP: Parameter-free Differentiable Pruning is All You Need
752. NeurIPS 2023Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning
753. NeurIPS 2023Preconditioning Matters: Fast Global Convergence of Non-convex Matrix Factorization via Scaled Gradient Descent
754. NeurIPS 2023Progressive Ensemble Distillation: Building Ensembles for Efficient Inference
755. NeurIPS 2023Provably Efficient Algorithm for Nonstationary Low-Rank MDPs
756. NeurIPS 2023Q-DM: An Efficient Low-bit Quantized Diffusion Model
757. NeurIPS 2023QLoRA: Efficient Finetuning of Quantized LLMs
758. NeurIPS 2023Rank-1 Matrix Completion with Gradient Descent and Small Random Initialization
759. NeurIPS 2023Rank-DETR for High Quality Object Detection
760. NeurIPS 2023Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares
761. NeurIPS 2023Res-Tuning: A Flexible and Efficient Tuning Paradigm via Unbinding Tuner from Backbone
762. NeurIPS 2023Robust low-rank training via approximate orthonormal constraints
763. NeurIPS 2023Robust Matrix Sensing in the Semi-Random Model
764. NeurIPS 2023Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
765. NeurIPS 2023Rubik's Cube: High-Order Channel Interactions with a Hierarchical Receptive Field
766. NeurIPS 2023Sharpness-Aware Minimization Leads to Low-Rank Features
767. NeurIPS 2023SODA: Robust Training of Test-Time Data Adaptors
768. NeurIPS 2023Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning
769. NeurIPS 2023Stable and low-precision training for large-scale vision-language models
770. NeurIPS 2023Statistical Limits of Adaptive Linear Models: Low-Dimensional Estimation and Inference
771. NeurIPS 2023Switching Autoregressive Low-rank Tensor Models
772. NeurIPS 2023The Geometry of Neural Nets' Parameter Spaces Under Reparametrization
773. NeurIPS 2023The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
774. NeurIPS 2023Towards Efficient and Accurate Winograd Convolution via Full Quantization
775. NeurIPS 2023Towards Higher Ranks via Adversarial Weight Pruning
776. NeurIPS 2023Transformed Low-Rank Parameterization Can Help Robust Generalization for Tensor Neural Networks
777. NeurIPS 2023Transformers learn through gradual rank increase
778. NeurIPS 2023Unbalanced Low-rank Optimal Transport Solvers
779. NeurIPS 2023Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
780. NeurIPS 2023Universality and Limitations of Prompt Tuning
781. NeurIPS 2023Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model

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.