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 12 of 17

551. ICML 2026Turning Back Without Forgetting: Selective Backward Refinement for Parameter-Efficient Continual Learning
552. ICML 2026TWLA: Achieving Ternary Weights and Low-Bit Activations for LLMs via Post-Training Quantization
553. ICML 2026U$^3$CF: Unbiased, Unconfounding, and Unified Causal Framework for Multi-Target Domain Adaptation
554. ICML 2026UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
555. ICML 2026Ultrafast On-Chip Online Learning via Spline Locality in Kolmogorov–Arnold Networks
556. ICML 2026Understanding Catastrophic Forgetting In LoRA via Mean-Field Attention Dynamics
557. ICML 2026Understanding LoRA as Knowledge Memory: An Empirical Analysis
558. ICML 2026UnHype: CLIP-Guided Hypernetworks for Dynamic LoRA Unlearning
559. ICML 2026Unifying Low Dimensional Spectra in Deep Learning
560. ICML 2026UniSVQ: 2-bit Unified Scalar-Vector Quantization
561. ICML 2026Video-SVD: Efficient Video Diffusion via Orthogonal Basis Composition
562. ICML 2026Weight Updates as Activation Shifts: A Principled Framework for Steering
563. ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
564. ICML 2026What Reward Structure Enables Efficient Sparse-Reward RL? A Proof-of-Concept with Policy-Aware Matrix Completion
565. ICML 2026When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control
566. ICML 2026When Is Rank-1 Enough? Geometry-Guided Initialization for Parameter-Efficient Fine-Tuning
567. ICML 2026When More Data Doesn't Help: Limits of Adaptation in Multitask Learning
568. ICML 2026WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
569. ICML 2026Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation
570. ICML 2026xKV: Cross-Layer KV-Cache Compression via Aligned Singular Vector Extraction
571. ICML 2026Zero Sum SVD: Balancing Loss Sensitivity for Low Rank LLM Compression
572. NeurIPS 2026(Mis)generalization of Helpful-Only Fine-Tuning
573. NeurIPS 2026$\delta$-Mem: : Efficient Online Memory For Large Language Models
574. NeurIPS 20263R-Adapter: Retrieval, Rewiring, and Refinement for Efficient Adaptation of 3D Reconstruction Model
575. NeurIPS 2026A low-rank decoder bottleneck bounds reliability in foundation-model perturbation prediction
576. NeurIPS 2026A Margin Perspective on LoRA: Robustness to Catastrophic Forgetting and Adapter Merging (MaLoRA)
577. NeurIPS 2026A Scalable Nonparametric Continuous-Time Survival Model through Numerical Quadrature
578. NeurIPS 2026A Sparse Low-Rank Biclique Decomposition for Graphs
579. NeurIPS 2026A unified pairwise distribution matching framework for graph domain adaptation under structure shift
580. NeurIPS 2026AdaPaD: Adaptive Parallel Deflation for PEFT with Self-Correcting Rank Discovery
581. NeurIPS 2026AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation
582. NeurIPS 2026Adapting in the Dark: Efficient and Stable Test-Time Adaptation for Black-Box Models
583. NeurIPS 2026Adaptive and Neutral Theory of Evolution Strategies for Large Language Models
584. NeurIPS 2026Adaptive Generate-Rank-Verify: Inference-Time Search with Costly Verification
585. NeurIPS 2026ADKV: A Low-Overhead Adaptive Delta Quantization for KV Cache in LLM Inference
586. NeurIPS 2026Advanced Routing as Regularization Allocation for Efficient Diffusion Transformer Training
587. NeurIPS 2026Align Before Aggregation: Basis-Consistent Federated LoRA under Heterogeneous Ranks
588. NeurIPS 2026Aligned LoRA Updates via Intrinsic Geometry for Federated Low-Rank Adaptation
589. NeurIPS 2026An Efficient Algorithm for Thresholding Monte Carlo Tree Search
590. NeurIPS 2026Anchor PCA
591. NeurIPS 2026Anchoring Physiological Invariance, Expanding Domain Plasticity: Prior-Stabilized Dynamic Adaptation for Continual rPPG Measurement
592. NeurIPS 2026Angular Networks: Low-Bit Learning from Randomized Similarity Estimators
593. NeurIPS 2026Approaching Effective Merging in Model Embedding Space
594. NeurIPS 2026Approximation in Contrastive Representation Learning
595. NeurIPS 2026AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning
596. NeurIPS 2026Archimedean Copula Inference via Taylor-Mode AD
597. NeurIPS 2026Asymmetric Factorization for Low-Rank PSD Learning: When Is the Relaxation Exact ?
598. NeurIPS 2026Attribute-Efficient Learning of Sparse Halfspaces with Constant Malicious Noise Rate
599. NeurIPS 2026Backdoor Attacks under Lossy Compression: From Failure to Reactivation and Adaptation
600. NeurIPS 2026Backdoor Purification for LoRA-Tuned LLMs via Null-Space Projection

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.