Low-Rank Adaptation papers, 2023–2026
LoRA and parameter-efficient tuning
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 2,273 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 78 | 76 | 65 | 63 | 282 |
| 2024 | 193 | 95 | 124 | 106 | 518 |
| 2025 | 241 | 152 | 136 | 103 | 632 |
| 2026 | 269 | 184 | 240 | 148 | 841 |
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 12 of 16
- NeurIPS 2024EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding
- NeurIPS 2024Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
- NeurIPS 2024Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games
- NeurIPS 2024Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
- NeurIPS 2024Efficient Discrepancy Testing for Learning with Distribution Shift
- NeurIPS 2024Efficient Lifelong Model Evaluation in an Era of Rapid Progress
- NeurIPS 2024Efficient LLM Scheduling by Learning to Rank
- NeurIPS 2024Efficient Minimum Bayes Risk Decoding using Low-Rank Matrix Completion Algorithms
- NeurIPS 2024Efficient Reinforcement Learning by Discovering Neural Pathways
- NeurIPS 2024EMGBench: Benchmarking Out-of-Distribution Generalization and Adaptation for Electromyography
- NeurIPS 2024Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
- NeurIPS 2024Entrywise error bounds for low-rank approximations of kernel matrices
- NeurIPS 2024Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
- NeurIPS 2024Expanding Sparse Tuning for Low Memory Usage
- NeurIPS 2024Exploring Low-Dimensional Subspace in Diffusion Models for Controllable Image Editing
- NeurIPS 2024F-OAL: Forward-only Online Analytic Learning with Fast Training and Low Memory Footprint in Class Incremental Learning
- NeurIPS 2024Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
- NeurIPS 2024Federated Black-Box Adaptation for Semantic Segmentation
- NeurIPS 2024Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
- NeurIPS 2024Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond
- NeurIPS 2024Fit for our purpose, not yours: Benchmark for a low-resource, Indigenous language
- NeurIPS 2024FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
- NeurIPS 2024FLoRA: Federated Fine-Tuning Large Language Models with Heterogeneous Low-Rank Adaptations
- NeurIPS 2024FouRA: Fourier Low-Rank Adaptation
- NeurIPS 2024From Dictionary to Tensor: A Scalable Multi-View Subspace Clustering Framework with Triple Information Enhancement
- NeurIPS 2024Frustratingly Easy Test-Time Adaptation of Vision-Language Models
- NeurIPS 2024Geometry-aware training of factorized layers in tensor Tucker format
- NeurIPS 2024Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing
- NeurIPS 2024Group and Shuffle: Efficient Structured Orthogonal Parametrization
- NeurIPS 2024Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing
- NeurIPS 2024Hollowed Net for On-Device Personalization of Text-to-Image Diffusion Models
- NeurIPS 2024How do Large Language Models Handle Multilingualism?
- NeurIPS 2024HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning
- NeurIPS 2024Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis
- NeurIPS 2024Improving Deep Learning Optimization through Constrained Parameter Regularization
- NeurIPS 2024Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
- NeurIPS 2024Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income Communities
- NeurIPS 2024Inferring stochastic low-rank recurrent neural networks from neural data
- NeurIPS 2024Instruction Tuning With Loss Over Instructions
- NeurIPS 2024IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution
- NeurIPS 2024Is Multiple Object Tracking a Matter of Specialization?
- NeurIPS 2024Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
- NeurIPS 2024KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization
- NeurIPS 2024L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
- NeurIPS 2024LaSCal: Label-Shift Calibration without target labels
- NeurIPS 2024Learn more, but bother less: parameter efficient continual learning
- NeurIPS 2024Learning De-Biased Representations for Remote-Sensing Imagery
- NeurIPS 2024Learning Discrete Latent Variable Structures with Tensor Rank Conditions
- NeurIPS 2024Learning Elastic Costs to Shape Monge Displacements
- NeurIPS 2024Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
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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.