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

840 papers, page 8 of 17

351. ICML 2026Beyond Description: Federated Adaptation via Semantic-Visual Prototype Alignment
352. ICML 2026Beyond Static Allocation: Dynamic Sensitivity-Aware Fine-Tuning for Vision Transformers
353. ICML 2026Beyond Structural Symmetries: Linear Mode Connectivity via Neuron Identifiability
354. ICML 2026Beyond Temperature: Hyperfitting as a Late-Stage Geometric Expansion
355. ICML 2026Biologically plausible heavy-tailed connectivity enhances generalizations on cognitive tasks in recurrent neural networks
356. ICML 2026Blocking the Leakage: Manifold-Aware Gradient Projection for Long-Horizon Test-Time Adaptation
357. ICML 2026Breaking the Computational Barrier: Provably Efficient Actor–Critic for Low-Rank MDPs
358. ICML 2026Bridging the Perceptual Gap: Residual-Enhanced Downscaling and Manifold-Aware Perception Alignment Adaptation for NR-IQA
359. ICML 2026Can Muon Fine-tune Adam-Pretrained Models?
360. ICML 2026Chebyshev Policies and the Mountain Car Problem: Reinforcement Learning for Low-Dimensional Control Tasks
361. ICML 2026Clipping Low-Probability Tokens in SFT Yields a Generalizable Initialization for RL
362. ICML 2026Clustering in Deep Stochastic Transformers
363. ICML 2026COBRA: Contribution-Based Bayesian Rank Allocation for Parameter-Efficient Fine-Tuning
364. ICML 2026CoLA: Cross-Modal Low-rank Adaptation for Multimodal Downstream Tasks
365. ICML 2026Collaborative and Efficient Fine-tuning: Leveraging Task Similarity
366. ICML 2026Compress then Merge: From Multiple LoRAs into One Low-Rank Adapter
367. ICML 2026Condition Number Based Low-Bit Quantization for Image Super-Resolution
368. ICML 2026Connecting Independently Trained Modes via Layer-Wise Connectivity
369. ICML 2026Convolutional Learnable-Group Weightless Neural Network
370. ICML 2026CRAMER: Control via Request-Aware Masking for Editing Recommenders
371. ICML 2026CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing
372. ICML 2026CSPLoRA: Confidence-Guided Structure Planning for Low-Rank Adaptation
373. ICML 2026cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
374. ICML 2026Dataset Distillation Efficiently Encodes Low-Dimensional Representations from Gradient-Based Learning of Non-Linear Tasks
375. ICML 2026Decoupled Low-Rank Adaptation for Robust Federated Fine-Tuning
376. ICML 2026Diffract: Spectral View of LLM Domain Adaptation
377. ICML 2026Diffusion Models Are Statistically Optimal for Learning Low-Dimensional Multi-Modal Distributions
378. ICML 2026Discretized Density-Guided Source-Free Domain Adaptation for Regression
379. ICML 2026Disentangling Geometry, Performance, and Training in Language Models
380. ICML 2026Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation
381. ICML 2026Diversity-aware Weight Perturbation Promotes Robust Adaptation
382. ICML 2026Diving into Kronecker Adapters: Component Design Matters
383. ICML 2026Doc-to-LoRA: Learning to Instantly Internalize Contexts
384. ICML 2026Domain Adaptation with Adaptive $f$-Divergence: Tighter Variational Representation and Generalization Bounds
385. ICML 2026Don't Reinvent the Wheel, Just Realign the Spokes: Resource-Efficient Federated Fine-Tuning via Rank-Wise Expert Assembly
386. ICML 2026Dynamic High-Dimensional Facility Location with Low Recourse
387. ICML 2026Efficient Multi-modal Dataset Distillation via Analytic Parameter Matching
388. ICML 2026Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning
389. ICML 2026Efficient, Validation-Free Intrinsic Quality Estimation for Large-Scale Face Recognition Datasets
390. ICML 2026Energy-Structured Low-Rank Adaptation for Continual Learning
391. ICML 2026Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation
392. ICML 2026Equivalence of Context and Parameter Updates in Modern Transformer Blocks
393. ICML 2026Escaping the Subspace Trap: The Role of Optimizer Geometry in Model Width Expansion
394. ICML 2026Evaluating Parameter Efficient Methods for RLVR
395. ICML 2026Exploring Data-Free LoRA Transferability for Video Diffusion Models
396. ICML 2026Extra-Merge: Tracing the Rank-1 Subspace of Model Merging in Language Model Pre-Training
397. ICML 2026Fast Spectrally Sparse Signal Reconstruction via Jacobi-Preconditioned Gradient Descent
398. ICML 2026Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
399. ICML 2026Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs
400. ICML 2026FedHera: Towards Drift-Resilient Federated Fine-tuning with Heterogeneous Resources

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.