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 16 of 17

751. NeurIPS 2026PGSB: Pretrained-Guided Shared Basis for LoRA Model Merging
752. NeurIPS 2026Pixels to Tokens: Token Space Efficient Active Learning for Low-Budget Semantic Segmentation
753. NeurIPS 2026PM-LoRA: Scalable Continual Learning via Progressive Merging of Low Rank Adapters
754. NeurIPS 2026PoEM: Predicting New RL Outcomes from Existing Policies
755. NeurIPS 2026POISE: Instance-Specific Prompt Tuning under Latent Mixture Target Distributions
756. NeurIPS 2026Prefix-Tuning for Arbitrary Output Sequences on Pretrained Transformers
757. NeurIPS 2026PreFT: Prefill-only finetuning for inference efficiency
758. NeurIPS 2026Primal-Dual Representation Learning for Low-Rank Constrained MDPs
759. NeurIPS 2026PRISM: Principal Subspace Alignment for Parameter-Efficient Fine-Tuning
760. NeurIPS 2026PRISM: Spectral Pruning and Reconstruction for Parameter-Efficient Model Merging of MLLMs
761. NeurIPS 2026PROLA: Principal-Orthogonal Low-rank Adaptation for Predictive Spatiotemporal Weather Downscaling
762. NeurIPS 2026Provably Efficient Representation Learning for Low-Rank CMDPs
763. NeurIPS 2026ProxySearch: Decoupled Inference-Time Scaling for Diffusion Models via Asymmetric Noise-Rank Transfer
764. NeurIPS 2026Prysma: Efficient Modality Adaptation for SLO-aware LLM-based Video Question Answering
765. NeurIPS 2026Quantifying Concentration Phenomena of Mean-Field Transformers in the Low-Temperature Regime
766. NeurIPS 2026Rank Is Not Capacity: Spectral Occupancy for Latent Graph Models
767. NeurIPS 2026Rank-Constrained Adaptation for Reliable Real-World Performance
768. NeurIPS 2026RankVQ: Low-Rank Parameterized Commutative Vector Quantization for KV Cache Compression
769. NeurIPS 2026RayTun3R: Online Camera Adaptation in 3D Foundation Models
770. NeurIPS 2026RECIPE: Learning to Rank Complete Precursor Sets for Inorganic Retrosynthesis
771. NeurIPS 2026Reconfiguring Procedural Knowledge for Compositional Robot Skill Adaptation
772. NeurIPS 2026Regret-Optimal Wasserstein-Robust Regression
773. NeurIPS 2026Relative Energy Barriers for Copyright-Aware Language Model Adaptation
774. NeurIPS 2026Reset Dependence Is Embodied: Training Protocol Changes Which Morphologies Appear Optimal
775. NeurIPS 2026Resource-Aware Parameter-Efficient Model Adaptation for Onboard High-Dimensional Data
776. NeurIPS 2026Rest-Tuning: Data-Efficient Adaptation of EEG Foundation Models to Individuals via Resting-State Signals
777. NeurIPS 2026Rethinking LLM Fine-Tuning via Weight Space Reparameterization: Preserving Safety during Downstream Adaptation
778. NeurIPS 2026Rich Insights from Cheap Signals: Efficient Evaluations via Tensor Factorization
779. NeurIPS 2026RIZZ: Routing Interactions to Near Zero-Interference Zones for Continual Adaptation of Black-Box Agents
780. NeurIPS 2026Robust Noisy Inductive Matrix Completion with Local Linear Convergence
781. NeurIPS 2026Route-Consistent Adaptation for Stable Quantization of Mixture-of-Experts Models with Theoretical Guarantees
782. NeurIPS 2026RubiConv - Efficient Boundary-Respecting Convolutions
783. NeurIPS 2026Safeguarding Mutual Correction in Source-Free Domain Adaptation via Cut Statistics
784. NeurIPS 2026SaMA: Morpho Adaptation via Asymmetric Expansion of Kronecker Product
785. NeurIPS 2026SARA: Step-Adaptive Rank Adjustment for Diffusion Inference Acceleration
786. NeurIPS 2026Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
787. NeurIPS 2026SD-LoRA: Training-Time Structural Distillation into LoRA for Few-Shot Vision-Language Adaptation
788. NeurIPS 2026SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation
789. NeurIPS 2026Seeking the Unfamiliar but Memorable: Conceptual Creativity as Meta-Learning
790. NeurIPS 2026Self-Tuning Graph Filters via State-Dependent Operator Composition
791. NeurIPS 2026Semantic-Statistical Prior Banks for Federated Low-Shot Learning under Non-IID Clients
792. NeurIPS 2026Sliced Wasserstein Meets Quantum Optics: Provable Wavefunctions Tomography with Scarce Noisy Measurements
793. NeurIPS 2026SpecBlock: Block-Iterative Speculative Decoding with Dynamic Tree Drafting
794. NeurIPS 2026SpecDrop: Parameter-Free Category-Conditioned Routing for Modular Specialization
795. NeurIPS 2026Spectral Alignment in Forward–Backward Representations via Temporal Abstraction
796. NeurIPS 2026Spectral Energy Allocation Enables Source-Free Domain Adaptation in Time Series Forecasting
797. NeurIPS 2026Spectral Rank Calibration for Continual LoRA Merging in Multimodal Large Language Models
798. NeurIPS 2026Spectral Reversal: Counteracting Singular Value Bias for Graph Prompting
799. NeurIPS 2026SPHQuant: Efficient extreme low bit weight quantization for Vision-Language Models
800. NeurIPS 2026Spike-SFT: Selective Parameter Enhancement and Fusion for Efficient Spiking Neural Networks

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.