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

269 papers, page 1 of 6

1. NeurIPS 2026(Mis)generalization of Helpful-Only Fine-Tuning
2. NeurIPS 2026$\delta$-Mem: : Efficient Online Memory For Large Language Models
3. NeurIPS 20263R-Adapter: Retrieval, Rewiring, and Refinement for Efficient Adaptation of 3D Reconstruction Model
4. NeurIPS 2026A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction
5. NeurIPS 2026A Margin Perspective on LoRA: Robustness to Catastrophic Forgetting and Adapter Merging (MaLoRA)
6. NeurIPS 2026A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature
7. NeurIPS 2026A Sparse Low-Rank Biclique Decomposition for Graphs
8. NeurIPS 2026A unified pairwise distribution matching framework for graph domain adaptation under structure shift
9. NeurIPS 2026AdaPaD: Adaptive Parallel Deflation for PEFT with Self-Correcting Rank Discovery
10. NeurIPS 2026AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation
11. NeurIPS 2026Adapting in the Dark: Efficient and Stable Test-Time Adaptation for Black-Box Models
12. NeurIPS 2026Adaptive and Neutral Theory of Evolution Strategies for Large Language Models
13. NeurIPS 2026Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification
14. NeurIPS 2026ADKV: A Low-Overhead Adaptive Delta Quantization for KV Cache in LLM Inference
15. NeurIPS 2026Advanced Routing as Regularization Allocation for Efficient Diffusion Transformer Training
16. NeurIPS 2026Align Before Aggregation: Basis-Consistent Federated LoRA under Heterogeneous Ranks
17. NeurIPS 2026Aligned LoRA Updates via Intrinsic Geometry for Federated Low-Rank Adaptation
18. NeurIPS 2026An Efficient Algorithm for Thresholding Monte Carlo Tree Search
19. NeurIPS 2026Anchor PCA
20. NeurIPS 2026Anchoring Physiological Invariance, Expanding Domain Plasticity: Prior-Stabilized Dynamic Adaptation for Continual rPPG Measurement
21. NeurIPS 2026Angular Networks: Low-Bit Learning from Randomized Similarity Estimators
22. NeurIPS 2026Approaching Effective Merging in Model Embedding Space
23. NeurIPS 2026Approximation in Contrastive Representation Learning
24. NeurIPS 2026AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning
25. NeurIPS 2026Archimedean Copula Inference via Taylor-Mode AD
26. NeurIPS 2026Asymmetric Factorization for Low-Rank PSD Learning: When Is the Relaxation Exact ?
27. NeurIPS 2026Attribute-Efficient Learning of Sparse Halfspaces with Constant Malicious Noise Rate
28. NeurIPS 2026Backdoor Attacks under Lossy Compression: From Failure to Reactivation and Adaptation
29. NeurIPS 2026Backdoor Purification for LoRA-Tuned LLMs via Null-Space Projection
30. NeurIPS 2026Batch-Conditioned Semantic Anchors for Robust Transductive Adaptation of Vision--Language Models
31. NeurIPS 2026Bayesian Low-Rank Posteriors for Scalable Membership Inference
32. NeurIPS 2026BDC-Merge: Cross-Architecture Model Merging via Dependency Alignment
33. NeurIPS 2026Benchmark Shadows: How Data Regimes Shape Parameter Footprints and Generalization
34. NeurIPS 2026Benchmarks as Measurement Instruments: Quantifying Signal and Noise for More Efficient AI Evaluations Under Distribution Shift
35. NeurIPS 2026Beyond High and Low: Evaluating Graded Cognitive Diversity in LLM Persona Simulations
36. NeurIPS 2026Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation
37. NeurIPS 2026Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
38. NeurIPS 2026Bilinear Matching Bandits
39. NeurIPS 2026BiLoCo: Binary Low-Rank Corrections for LLM FP4 Decode
40. NeurIPS 2026BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
41. NeurIPS 2026BQ-LoRA: Binary-Quantized Low-Rank Adapters as Implicit Regularizers for Parameter-Efficient Fine-Tuning
42. NeurIPS 2026Breaking Information Islands in Sparse Tuning via Small-World Connectivity
43. NeurIPS 2026BReD: Block Replay Dithering for Stable Low-Bit EMA Optimizer States
44. NeurIPS 2026Bridging Sequence and Structure with Unified Domain Adaptation for Drug-Target Interaction Prediction
45. NeurIPS 2026Can Model Merging Improve Aggregation in DiLoCo?
46. NeurIPS 2026Causal Discovery via Transformed Low-Rank Quantile Surfaces
47. NeurIPS 2026CC-GS: Low-Memory 3D Gaussian Splatting Training via CPU-GPU Block-Wise Context Compositing
48. NeurIPS 2026Class-Incremental Learning via LoRA-based Elastic Ensemble of Experts
49. NeurIPS 2026ClusQuant: Mitigating Outliers with Clustering-Based Representations for Low-Precision LRMs
50. NeurIPS 2026Communication-Efficient LLM Adaptation over Decentralized GPU Meshes

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.