Learning to Rank papers, 2023–2026
LTR models
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 257 papers are tagged with this topic.
Key findings
- Learning to Rank fell from 142 papers in 2023 to 55 in 2026, so interest is cooling.
- NeurIPS publishes the most Learning to Rank work: 154 papers from 2023 to 2026, 60% of the four-venue total.
- The fastest-growing overlap is with Low-Rank Adaptation: papers tagged with both rose from 39 in 2023 to 43 in 2026.
- Among the 5 topics under Information Retrieval, it ranks #4 by 2026 paper count; the fastest grower in the group, Cross-Encoder Reranking, is up 3.0x versus 0.4x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 112 | 4 | 25 | 1 | 142 |
| 2024 | 11 | 2 | 12 | 3 | 28 |
| 2025 | 13 | 8 | 10 | 1 | 32 |
| 2026 | 18 | 9 | 26 | 2 | 55 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank
- ICML 2026From Per-Image Low-Rank to Encoding Mismatch: Rethinking Feature Distillation in Vision Transformers
- ICLR 2026Designing Rules to Pick a Rule: Aggregation by Consistency
- CVPR 2026LRDUN A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive
- NeurIPS 2025From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics
- ICML 2025Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
- ICLR 2025Palu: KV-Cache Compression with Low-Rank Projection
- CVPR 2025Breaking the Low-Rank Dilemma of Linear Attention
- NeurIPS 2024Efficient LLM Scheduling by Learning to Rank
- ICML 2024Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
- ICLR 2024LQ-LoRA: Low-rank plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
- CVPR 2024Tuning Stable Rank Shrinkage: Aiming at the Overlooked Structural Risk in Fine-tuning
- NeurIPS 2023A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games
- ICML 2023Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning
- ICLR 2023Implicit Bias of Large Depth Networks: a Notion of Rank for Nonlinear Functions
- CVPR 20231% VS 100%: Parameter-Efficient Low Rank Adapter for Dense Predictions
- NeurIPS 2026Matrix Recovery Via Symmetric Rank-one Measurements With Random Unit-modulus Vectors
- ICML 2026The Generalization Spectrum: A Chromatographic Approach to Evaluating Learning Algorithms
- ICLR 2026Revisiting Weight Regularization for Low-Rank Continual Learning
- CVPR 2026Low-Rank Residual Diffusion Models
All Learning to Rank papers
13 papers, page 1 of 1
- NeurIPS 2025A geometric framework for momentum-based optimizers for low-rank training
- NeurIPS 2025AuroRA: Breaking Low-Rank Bottleneck of LoRA with Nonlinear Mapping
- NeurIPS 2025Demystifying Language Model Forgetting with Low-rank Example Associations
- NeurIPS 2025Efficient Low Rank Attention for Long-Context Inference in Large Language Models
- NeurIPS 2025Fira: Can We Achieve Full-rank Training of LLMs Under Low-rank Constraint?
- NeurIPS 2025From Condensation to Rank Collapse: A Two-Stage Analysis of Transformer Training Dynamics
- NeurIPS 2025Generalization Bounds for Rank-sparse Neural Networks
- NeurIPS 2025LittleBit: Ultra Low-Bit Quantization via Latent Factorization
- NeurIPS 2025Low-Rank Graphon Learning for Networks
- NeurIPS 2025Low-Rank Head Avatar Personalization with Registers
- NeurIPS 2025On the Role of Hidden States of Modern Hopfield Network in Transformer
- NeurIPS 2025Perturbation Bounds for Low-Rank Inverse Approximations under Noise
- NeurIPS 2025Q3R: Quadratic Reweighted Rank Regularizer for Effective Low-Rank Training
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FAQ
- How many Learning to Rank papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 257 in total: 142 in 2023, 28 in 2024, 32 in 2025, 55 in 2026.
- How many Learning to Rank papers are at NeurIPS 2026?
- NeurIPS 2026 has 18 Learning to Rank papers, versus 13 the year before.
- How many Learning to Rank papers are at ICLR 2026?
- ICLR 2026 has 9 Learning to Rank papers, versus 8 the year before.
- How many Learning to Rank papers are at ICML 2026?
- ICML 2026 has 26 Learning to Rank papers, versus 10 the year before.
- How many Learning to Rank papers are at CVPR 2026?
- CVPR 2026 has 2 Learning to Rank papers, versus 1 the year before.
- Which conference publishes the most Learning to Rank papers?
- NeurIPS, with 154 papers from 2023 to 2026.