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 13 of 17

601. NeurIPS 2026Batch-Conditioned Semantic Anchors for Robust Transductive Adaptation of Vision--Language Models
602. NeurIPS 2026Bayesian Low-Rank Posteriors for Scalable Membership Inference
603. NeurIPS 2026BDC-Merge: Cross-Architecture Model Merging via Dependency Alignment
604. NeurIPS 2026Benchmark Shadows: How Data Regimes Shape Parameter Footprints and Generalization
605. NeurIPS 2026Benchmarks as Measurement Instruments: Quantifying Signal and Noise for More Efficient AI Evaluations Under Distribution Shift
606. NeurIPS 2026Beyond High and Low: Evaluating Graded Cognitive Diversity in LLM Persona Simulations
607. NeurIPS 2026Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation
608. NeurIPS 2026Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
609. NeurIPS 2026Bilinear Matching Bandits
610. NeurIPS 2026BiLoCo: Binary Low-Rank Corrections for LLM FP4 Decode
611. NeurIPS 2026BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
612. NeurIPS 2026BQ-LoRA: Binary-Quantized Low-Rank Adapters as Implicit Regularizers for Parameter-Efficient Fine-Tuning
613. NeurIPS 2026Breaking Information Islands in Sparse Tuning via Small-World Connectivity
614. NeurIPS 2026BReD: Block Replay Dithering for Stable Low-Bit EMA Optimizer States
615. NeurIPS 2026Bridging Sequence and Structure with Unified Domain Adaptation for Drug-Target Interaction Prediction
616. NeurIPS 2026Can Model Merging Improve Aggregation in DiLoCo?
617. NeurIPS 2026Causal Discovery via Transformed Low-Rank Quantile Surfaces
618. NeurIPS 2026CC-GS: Low-Memory 3D Gaussian Splatting Training via CPU-GPU Block-Wise Context Compositing
619. NeurIPS 2026Class-Incremental Learning via LoRA-based Elastic Ensemble of Experts
620. NeurIPS 2026ClusQuant: Mitigating Outliers with Clustering-Based Representations for Low-Precision LRMs
621. NeurIPS 2026Communication-Efficient LLM Adaptation over Decentralized GPU Meshes
622. NeurIPS 2026Communication-Efficient Personalized Adaptation via Federated-Local Model Merging
623. NeurIPS 2026Comp$^2$VLM: A Hybrid Framework Combining Quantization and Lossless Compression for Efficient Vision-Language Models
624. NeurIPS 2026Complementary Cache Guidance with Gradient Disentanglement for Continuous Test-Time Adaptation
625. NeurIPS 2026Complexity-Aware LoRA Aggregation for Modality-Heterogeneous Federated Person Re-identification
626. NeurIPS 2026Confidence-Based Decoding is Provably Efficient for Diffusion Language Models
627. NeurIPS 2026Context as Low-Rank Weights: Bounded Parametric Dynamic Memory for Unbounded Context
628. NeurIPS 2026Continuous Expert Assembly: Instance-Conditioned Low-Rank Residuals for All-in-One Image Restoration
629. NeurIPS 2026Controlling Temporal Pseudo-Label Marginals for Stable Online Test-Time Adaptation
630. NeurIPS 2026Convergence of Near-Linear Width ReLU Networks with Unbalanced Initialization
631. NeurIPS 2026CORA: Per-Slice Coherent Orthogonal Rotation for SVD-based Low-Rank Adaptation
632. NeurIPS 2026CPA: Efficient and Stable FP4 RL Training via Cross-Precision Alignment
633. NeurIPS 2026D-DOIT: Training-free Adaptation of Discrete Diffusion via Doob's h-Transform
634. NeurIPS 2026D$^2$Quant: Accurate Low-bit Post-Training Weight Quantization for LLMs
635. NeurIPS 2026DAGA: Dynamic Attention-Guided Adaptation for Self-Supervised Vision Transformers
636. NeurIPS 2026Decomposing the modulation of interactions between neuronal populations
637. NeurIPS 2026DEDCA: Test-Time Adaptation for Generalized AI-Generated Image Detection
638. NeurIPS 2026DeltaMomentum: A Key-Value based Anisotropic Momentum Update via Delta Rule
639. NeurIPS 2026Depth through Recurrence: Towards Ultra-Efficient On-Device ASR
640. NeurIPS 2026DiffATS: Diffusion in Aligned Tensor Space
641. NeurIPS 2026Diffusion Tree Search for Inference Time Adaptation of Material Foundation Models
642. NeurIPS 2026Dominant-Layer ZO: A Single Layer Dominates Zeroth-Order Fine-Tuning of LLMs
643. NeurIPS 2026Don’t Learn What You Can Compute: Arithmetic Residual Blocks for Exact Arithmetic in Transformers
644. NeurIPS 2026Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank
645. NeurIPS 2026DRIVE: Fine-tuning via Data Contribution- and Diversity-aware Weighting with Prior Regularization
646. NeurIPS 2026Dual-Pronged LoRA: Achieving Near-Zero Forgetting and High-Performance Adaptation for MLLMs
647. NeurIPS 2026Dynamic Model Merging Made Slim
648. NeurIPS 2026Dynamics of the Transformer Residual Stream: Coupling Spectral Geometry to Network Topology
649. NeurIPS 2026DyRA: Dynamic Residual Approximation for Efficient Matrix Multiplication in DNNs
650. NeurIPS 2026Editing Large Language Models with Geometry-Aware Regularization

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.