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

781 papers, page 13 of 16

601. NeurIPS 2024Learning from Offline Foundation Features with Tensor Augmentations
602. NeurIPS 2024Learning Low-Rank Feature for Thorax Disease Classification
603. NeurIPS 2024Leveraging partial stragglers within gradient coding
604. NeurIPS 2024LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages
605. NeurIPS 2024LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
606. NeurIPS 2024LoFiT: Localized Fine-tuning on LLM Representations
607. NeurIPS 2024Loki: Low-rank Keys for Efficient Sparse Attention
608. NeurIPS 2024Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution Adaptation
609. NeurIPS 2024LoQT: Low-Rank Adapters for Quantized Pretraining
610. NeurIPS 2024LoRA-GA: Low-Rank Adaptation with Gradient Approximation
611. NeurIPS 2024LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search
612. NeurIPS 2024Low Degree Hardness for Broadcasting on Trees
613. NeurIPS 2024Low Precision Local Training is Enough for Federated Learning
614. NeurIPS 2024Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
615. NeurIPS 2024LuSh-NeRF: Lighting up and Sharpening NeRFs for Low-light Scenes
616. NeurIPS 2024MambaLLIE: Implicit Retinex-Aware Low Light Enhancement with Global-then-Local State Space
617. NeurIPS 2024Memory-Efficient LLM Training with Online Subspace Descent
618. NeurIPS 2024Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
619. NeurIPS 2024Metric Transforms and Low Rank Representations of Kernels for Fast Attention
620. NeurIPS 2024MKGL: Mastery of a Three-Word Language
621. NeurIPS 2024Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
622. NeurIPS 2024Multistable Shape from Shading Emerges from Patch Diffusion
623. NeurIPS 2024Neural collapse vs. low-rank bias: Is deep neural collapse really optimal?
624. NeurIPS 2024Neural Embeddings Rank: Aligning 3D latent dynamics with movements
625. NeurIPS 2024Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit
626. NeurIPS 2024NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes
627. NeurIPS 2024Nimbus: Secure and Efficient Two-Party Inference for Transformers
628. NeurIPS 2024No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
629. NeurIPS 2024Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks
630. NeurIPS 2024Nuclear Norm Regularization for Deep Learning
631. NeurIPS 2024Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation
632. NeurIPS 2024On $f$-Divergence Principled Domain Adaptation: An Improved Framework
633. NeurIPS 2024On Socially Fair Low-Rank Approximation and Column Subset Selection
634. NeurIPS 2024On Sparse Canonical Correlation Analysis
635. NeurIPS 2024On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)
636. NeurIPS 2024OneBit: Towards Extremely Low-bit Large Language Models
637. NeurIPS 2024Online Adaptation of Language Models with a Memory of Amortized Contexts
638. NeurIPS 2024Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
639. NeurIPS 2024Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives
640. NeurIPS 2024OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
641. NeurIPS 2024PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization
642. NeurIPS 2024Panacea: Pareto Alignment via Preference Adaptation for LLMs
643. NeurIPS 2024Parameter Competition Balancing for Model Merging
644. NeurIPS 2024Parameter Efficient Adaptation for Image Restoration with Heterogeneous Mixture-of-Experts
645. NeurIPS 2024Parameter-free Clipped Gradient Descent Meets Polyak
646. NeurIPS 2024Personalized Federated Learning via Feature Distribution Adaptation
647. NeurIPS 2024PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language Models
648. NeurIPS 2024Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation
649. NeurIPS 2024Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context
650. NeurIPS 2024PrivAuditor: Benchmarking Data Protection Vulnerabilities in LLM Adaptation Techniques

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.