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 9 of 11

401. NeurIPS 2024Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation
402. NeurIPS 2024Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income Communities
403. NeurIPS 2024Inferring stochastic low-rank recurrent neural networks from neural data
404. NeurIPS 2024Instruction Tuning With Loss Over Instructions
405. NeurIPS 2024IODA: Instance-Guided One-shot Domain Adaptation for Super-Resolution
406. NeurIPS 2024Is Multiple Object Tracking a Matter of Specialization?
407. NeurIPS 2024Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
408. NeurIPS 2024KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization
409. NeurIPS 2024L-TTA: Lightweight Test-Time Adaptation Using a Versatile Stem Layer
410. NeurIPS 2024LaSCal: Label-Shift Calibration without target labels
411. NeurIPS 2024Learn more, but bother less: parameter efficient continual learning
412. NeurIPS 2024Learning De-Biased Representations for Remote-Sensing Imagery
413. NeurIPS 2024Learning Discrete Latent Variable Structures with Tensor Rank Conditions
414. NeurIPS 2024Learning Elastic Costs to Shape Monge Displacements
415. NeurIPS 2024Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks
416. NeurIPS 2024Learning from Offline Foundation Features with Tensor Augmentations
417. NeurIPS 2024Learning Low-Rank Feature for Thorax Disease Classification
418. NeurIPS 2024Leveraging partial stragglers within gradient coding
419. NeurIPS 2024LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages
420. NeurIPS 2024LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
421. NeurIPS 2024LoFiT: Localized Fine-tuning on LLM Representations
422. NeurIPS 2024Loki: Low-rank Keys for Efficient Sparse Attention
423. NeurIPS 2024Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
424. NeurIPS 2024LoQT: Low-Rank Adapters for Quantized Pretraining
425. NeurIPS 2024LoRA-GA: Low-Rank Adaptation with Gradient Approximation
426. NeurIPS 2024LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
427. NeurIPS 2024Low Degree Hardness for Broadcasting on Trees
428. NeurIPS 2024Low Precision Local Training is Enough for Federated Learning
429. NeurIPS 2024Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
430. NeurIPS 2024LuSh-NeRF: Lighting up and Sharpening NeRFs for Low-light Scenes
431. NeurIPS 2024MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space
432. NeurIPS 2024Memory-Efficient LLM Training with Online Subspace Descent
433. NeurIPS 2024Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
434. NeurIPS 2024Metric Transforms and Low Rank Representations of Kernels for Fast Attention
435. NeurIPS 2024MKGL: Mastery of a Three-Word Language
436. NeurIPS 2024Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
437. NeurIPS 2024Multistable Shape from Shading Emerges from Patch Diffusion
438. NeurIPS 2024Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?
439. NeurIPS 2024Neural Embeddings Rank: Aligning 3D latent dynamics with movements
440. NeurIPS 2024Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit
441. NeurIPS 2024NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes
442. NeurIPS 2024Nimbus: Secure and Efficient Two-Party Inference for Transformers
443. NeurIPS 2024No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
444. NeurIPS 2024Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks
445. NeurIPS 2024Nuclear Norm Regularization for Deep Learning
446. NeurIPS 2024Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
447. NeurIPS 2024On $f$-Divergence Principled Domain Adaptation: An Improved Framework
448. NeurIPS 2024On Socially Fair Low-Rank Approximation and Column Subset Selection
449. NeurIPS 2024On Sparse Canonical Correlation Analysis
450. NeurIPS 2024On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)

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.