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 35 of 46

1701. ICML 2024Differentially Private Domain Adaptation with Theoretical Guarantees
1702. ICML 2024DiJiang: Efficient Large Language Models through Compact Kernelization
1703. ICML 2024DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models
1704. ICML 2024Do Efficient Transformers Really Save Computation?
1705. ICML 2024DoRA: Weight-Decomposed Low-Rank Adaptation
1706. ICML 2024DPZero: Private Fine-Tuning of Language Models without Backpropagation
1707. ICML 2024E$^2$GAN: Efficient Training of Efficient GANs for Image-to-Image Translation
1708. ICML 2024EDISON: Enhanced Dictionary-Induced Tensorized Incomplete Multi-View Clustering with Gaussian Error Rank Minimization
1709. ICML 2024Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
1710. ICML 2024Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits
1711. ICML 2024Efficient Non-stationary Online Learning by Wavelets with Applications to Online Distribution Shift Adaptation
1712. ICML 2024Efficient Pareto Manifold Learning with Low-Rank Structure
1713. ICML 2024Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
1714. ICML 2024Error Feedback Can Accurately Compress Preconditioners
1715. ICML 2024ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
1716. ICML 2024Evaluation of Test-Time Adaptation Under Computational Time Constraints
1717. ICML 2024Exploring the Low-Pass Filtering Behavior in Image Super-Resolution
1718. ICML 2024Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
1719. ICML 2024Fast White-Box Adversarial Streaming Without a Random Oracle
1720. ICML 2024Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training
1721. ICML 2024FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models
1722. ICML 2024Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
1723. ICML 2024FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
1724. ICML 2024Feedback Efficient Online Fine-Tuning of Diffusion Models
1725. ICML 2024Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings
1726. ICML 2024FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction
1727. ICML 2024Flora: Low-Rank Adapters Are Secretly Gradient Compressors
1728. ICML 2024FrameQuant: Flexible Low-Bit Quantization for Transformers
1729. ICML 2024From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuning
1730. ICML 2024GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
1731. ICML 2024Gated Linear Attention Transformers with Hardware-Efficient Training
1732. ICML 2024Generalization Analysis of Deep Non-linear Matrix Completion
1733. ICML 2024Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
1734. ICML 2024Getting the most out of your tokenizer for pre-training and domain adaptation
1735. ICML 2024GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding
1736. ICML 2024Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method
1737. ICML 2024Harmonizing Generalization and Personalization in Federated Prompt Learning
1738. ICML 2024Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
1739. ICML 2024High-Dimensional Geometric Streaming for Nearly Low Rank Data
1740. ICML 2024Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
1741. ICML 2024IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
1742. ICML 2024IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation
1743. ICML 2024Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
1744. ICML 2024Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
1745. ICML 2024Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
1746. ICML 2024LESS: Selecting Influential Data for Targeted Instruction Tuning
1747. ICML 2024Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
1748. ICML 2024LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
1749. ICML 2024LoRA Training in the NTK Regime has No Spurious Local Minima
1750. ICML 2024LoRA+: Efficient Low Rank Adaptation of Large Models

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.