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 15 of 17

701. NeurIPS 2026Knowing When Multivariate Forecasts Are Wrong
702. NeurIPS 2026LAMP: Look-Ahead Mixed-Precision Inference of Large Language Models
703. NeurIPS 2026Language-Induced Priors for Domain Adaptation
704. NeurIPS 2026LAPLEX: The FFT of Learnable Laplace Kernels
705. NeurIPS 2026LAtte: Hyperbolic Lorentz Attention for Joint-Subject EEG Classification
706. NeurIPS 2026LEAN: Library-Based Adaptation for Asynchronous, Federated Fine-Tuning
707. NeurIPS 2026Learnable Low-Rank Polynomial Sketch for Effective Linear Attention
708. NeurIPS 2026Learning a Task-Adaptive Low-Dimensional Semantic Space for Improved Visual Classification
709. NeurIPS 2026Learning from Ranking Feedback: Improved Regret Bounds via Independence Preserving Rank Breaking
710. NeurIPS 2026Learning Process Rewards via Visitation Matching for Efficient RL
711. NeurIPS 2026Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning
712. NeurIPS 2026Learning Reveals Invisible Structure in Low-Rank RNNs
713. NeurIPS 2026Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation
714. NeurIPS 2026LENS: Low-Frequency Eigen Noise Shaping for Efficient Diffusion Sampling
715. NeurIPS 2026Locking Pretrained Weights via Deep Low-Rank Residual Distillation
716. NeurIPS 2026LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
717. NeurIPS 2026LoRASpace: A Pool-Wide Shared Substrate for Static and Dynamic Multi-LoRA Composition
718. NeurIPS 2026LoRAtorio: An intrinsic approach to LoRA Skill Composition
719. NeurIPS 2026Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
720. NeurIPS 2026Low-Rank Hierarchical Merging for Efficient Long-to-Short Reasoning
721. NeurIPS 2026LR-V2X: Loss Resilient Collaborative Perception under Low-Bandwidth Communication
722. NeurIPS 2026LSVD: Loss-Aware Low-Rank Approximation for Efficient Low-Precision Vision-Language Models
723. NeurIPS 2026Magnitude-preserving Layers Enable Efficient GANs
724. NeurIPS 2026Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
725. NeurIPS 2026MaPP: A Unified Marginalized Posterior-Predictive Framework for Data-Efficient RLVR
726. NeurIPS 2026MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models
727. NeurIPS 2026MARS: Harmonizing Multimodal Convergence via Adaptive Rank Search
728. NeurIPS 2026Match the Geometry, Skip the Surrogate: Extreme Low-Budget Optimization in High Dimensions
729. NeurIPS 2026Matrix Recovery Via Symmetric Rank-one Measurements With Random Unit-modulus Vectors
730. NeurIPS 2026Matrix-Free Stochastic Training of Low-Rank Spectral Graph Learning via Randomized Adaptive Spectral Estimation
731. NeurIPS 2026Metric Depth Estimation from Arbitrarily Degraded Low-Resolution Depth Prompts
732. NeurIPS 2026MIRA: Mutual Information guided calibration for Reliable Test-Time Adaptation
733. NeurIPS 2026Modulating Merging Strengths via Joint Loss Estimation for LoRA-based Continual Learning
734. NeurIPS 2026Morpho-Temporal Decoupling: How Primate Neurons Expand Dendrites Without Losing Speed
735. NeurIPS 2026NoTA: Normalized Tensor Adaptation for Parameter-Efficient Continual Learning
736. NeurIPS 2026NoTVLA: Semantics-Preserving Robot Adaptation via Narrative Action Interfaces
737. NeurIPS 2026NP-LoRA: Null Space Projection for Subject-Style LoRA Fusion
738. NeurIPS 2026On JEPA Isotropy
739. NeurIPS 2026On the Construction and Implications of Low-Loss Valleys in LoRA-based Bayesian Inference
740. NeurIPS 2026On the Geometry and Latent-Space Composition of Hypernetwork-Generated LoRAs
741. NeurIPS 2026On the Limits of Latent Reuse in Diffusion Models
742. NeurIPS 2026One Algorithm, Two Goals: Dual Scoring for Parameter and Data Selection in LLM Fine-Tuning
743. NeurIPS 2026One Scan is Enough: Demonstration-Free Adaptation for Language-Guided Navigation
744. NeurIPS 2026OrbitLoRA: Learning Rotation-Aware Low-Data Adaptation of Vision Foundation Models
745. NeurIPS 2026Overcoming Rank Collapse in Feedback Alignment
746. NeurIPS 2026Pandora's AI Model Routing Box: Efficient Allocation with Costly Value Estimation
747. NeurIPS 2026Parameter symmetries determine representational geometry in overparameterized nonlinear networks
748. NeurIPS 2026Path Dependence under Adaptive AI Delegation
749. NeurIPS 2026Pattern-Based Matrix Analysis Under Permutations
750. NeurIPS 2026Permute-then-Adapt: Weak-to-Strong Contrastive Image--Text Adaptation

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.