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 40 of 46

1951. NeurIPS 2024SeTAR: Out-of-Distribution Detection with Selective Low-Rank Approximation
1952. NeurIPS 2024SGD vs GD: Rank Deficiency in Linear Networks
1953. NeurIPS 2024Shaping the distribution of neural responses with interneurons in a recurrent circuit model
1954. NeurIPS 2024Sharing Key Semantics in Transformer Makes Efficient Image Restoration
1955. NeurIPS 2024Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts
1956. NeurIPS 2024Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information
1957. NeurIPS 2024Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
1958. NeurIPS 2024SLTrain: a sparse plus low rank approach for parameter and memory efficient pretraining
1959. NeurIPS 2024SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead
1960. NeurIPS 2024Sparse High Rank Adapters
1961. NeurIPS 2024Spectral Adapter: Fine-Tuning in Spectral Space
1962. NeurIPS 2024SpeedLoader: An I/O efficient scheme for heterogeneous and distributed LLM operation
1963. NeurIPS 2024Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks
1964. NeurIPS 2024SSDiff: Spatial-spectral Integrated Diffusion Model for Remote Sensing Pansharpening
1965. NeurIPS 2024Stepping Forward on the Last Mile
1966. NeurIPS 2024Structured flexibility in recurrent neural networks via neuromodulation
1967. NeurIPS 2024Structured Unrestricted-Rank Matrices for Parameter Efficient Finetuning
1968. NeurIPS 2024SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
1969. NeurIPS 2024Swift Sampler: Efficient Learning of Sampler by 10 Parameters
1970. NeurIPS 2024Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor
1971. NeurIPS 2024Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line
1972. NeurIPS 2024The Impact of Initialization on LoRA Finetuning Dynamics
1973. NeurIPS 2024The Ladder in Chaos: Improving Policy Learning by Harnessing the Parameter Evolving Path in A Low-dimensional Space
1974. NeurIPS 2024The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure
1975. NeurIPS 2024Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning
1976. NeurIPS 2024Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models
1977. NeurIPS 2024TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices
1978. NeurIPS 2024Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming
1979. NeurIPS 2024Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learner
1980. NeurIPS 2024Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective
1981. NeurIPS 2024Unrolled denoising networks provably learn to perform optimal Bayesian inference
1982. NeurIPS 2024Unveiling LoRA Intrinsic Ranks via Salience Analysis
1983. NeurIPS 2024VB-LoRA: Extreme Parameter Efficient Fine-Tuning with Vector Banks
1984. NeurIPS 2024VeLoRA: Memory Efficient Training using Rank-1 Sub-Token Projections
1985. NeurIPS 2024VFIMamba: Video Frame Interpolation with State Space Models
1986. NeurIPS 2024Visual Fourier Prompt Tuning
1987. NeurIPS 2024Weight decay induces low-rank attention layers
1988. NeurIPS 2024Who’s Gaming the System? A Causally-Motivated Approach for Detecting Strategic Adaptation
1989. NeurIPS 2024You Only Look Around: Learning Illumination-Invariant Feature for Low-light Object Detection
1990. NeurIPS 2024Zero-Shot Reinforcement Learning from Low Quality Data
1991. CVPR 20231% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions
1992. CVPR 2023A Probabilistic Framework for Lifelong Test-Time Adaptation
1993. CVPR 2023A-La-Carte Prompt Tuning (APT): Combining Distinct Data via Composable Prompting
1994. CVPR 2023Adapting Shortcut With Normalizing Flow: An Efficient Tuning Framework for Visual Recognition
1995. CVPR 2023ALOFT: A Lightweight MLP-Like Architecture With Dynamic Low-Frequency Transform for Domain Generalization
1996. CVPR 2023Boosting Low-Data Instance Segmentation by Unsupervised Pre-Training With Saliency Prompt
1997. CVPR 2023C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation
1998. CVPR 2023Class Relationship Embedded Learning for Source-Free Unsupervised Domain Adaptation
1999. CVPR 2023Cloud-Device Collaborative Adaptation to Continual Changing Environments in the Real-World
2000. CVPR 2023COT: Unsupervised Domain Adaptation With Clustering and Optimal Transport

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.