Deep learning · representation learning papers, 2023–2026

Key findings

• Deep learning · representation learning fell from 259 papers in 2023 to 214 in 2026, so interest is cooling.
• NeurIPS publishes the most Deep learning · representation learning work: 279 papers from 2023 to 2026, 35% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 11 in 2023 to 28 in 2026.
• Among the 11 topics under Deep Learning, it ranks #7 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 0.8x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
• ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
• ICLR 2026Boosting Open Set Recognition Performance through Modulated Representation Learning
• CVPR 2026CanonCGT Reference-Based Color Grading via Canonical Pivot Representation
• NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
• ICML 2025Banyan: Improved Representation Learning with Explicit Structure
• ICLR 2025Edge-aware Image Smoothing with Relative Wavelet Domain Representation
• CVPR 20253D-SLNR: A Super Lightweight Neural Representation for Large-scale 3D Mapping
• NeurIPS 2024GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
• ICML 2024Data-free Neural Representation Compression with Riemannian Neural Dynamics
• ICLR 2024$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
• CVPR 2024Disentangled Prompt Representation for Domain Generalization
• NeurIPS 2023[Re] CrossWalk: Fairness-enhanced Node Representation Learning
• ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
• ICLR 2023Bispectral Neural Networks
• CVPR 2023AnyFlow: Arbitrary Scale Optical Flow With Implicit Neural Representation
• NeurIPS 2026Approximation in Contrastive Representation Learning
• ICML 2026Amortized Maximum Inner Product Search with Learned Support Functions
• ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
• CVPR 2026Enhancing Visual Representation with Textual Semantics Textual Semantics-Powered Prototypes for

All Deep learning · representation learning papers

58 papers, page 1 of 2

1. ICLR 2023Actionable Neural Representations: Grid Cells from Minimal Constraints
2. ICLR 2023Advancing Radiograph Representation Learning with Masked Record Modeling
3. ICLR 2023Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
4. ICLR 2023Are More Layers Beneficial to Graph Transformers?
5. ICLR 2023Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
6. ICLR 2023Behavior Prior Representation learning for Offline Reinforcement Learning
7. ICLR 2023Bispectral Neural Networks
8. ICLR 2023BrainBERT: Self-supervised representation learning for intracranial recordings
9. ICLR 2023Constructive TT-representation of the tensors given as index interaction functions with applications
10. ICLR 2023Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
11. ICLR 2023DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
12. ICLR 2023Differentiable Mathematical Programming for Object-Centric Representation Learning
13. ICLR 2023Disentanglement of Correlated Factors via Hausdorff Factorized Support
14. ICLR 2023Disentangling Learning Representations with Density Estimation
15. ICLR 2023Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
16. ICLR 2023Efficient Conditionally Invariant Representation Learning
17. ICLR 2023Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning
18. ICLR 2023Evaluating Representations with Readout Model Switching
19. ICLR 2023Finding the Global Semantic Representation in GAN through Fréchet Mean
20. ICLR 2023Gromov-Wasserstein Autoencoders
21. ICLR 2023How robust is unsupervised representation learning to distribution shift?
22. ICLR 2023Hyperbolic Deep Reinforcement Learning
23. ICLR 2023Improving Out-of-distribution Generalization with Indirection Representations
24. ICLR 2023Is a Caption Worth a Thousand Images? A Study on Representation Learning
25. ICLR 2023Language Modelling with Pixels
26. ICLR 2023Latent Variable Representation for Reinforcement Learning
27. ICLR 2023Learning Domain-Agnostic Representation for Disease Diagnosis
28. ICLR 2023Learning Language Representations with Logical Inductive Bias
29. ICLR 2023Learning Structured Representations by Embedding Class Hierarchy
30. ICLR 2023Learning topology-preserving data representations
31. ICLR 2023Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
32. ICLR 2023Logical Message Passing Networks with One-hop Inference on Atomic Formulas
33. ICLR 2023Mitigating Memorization of Noisy Labels via Regularization between Representations
34. ICLR 2023Multivariate Time-series Imputation with Disentangled Temporal Representations
35. ICLR 2023Neural Implicit Shape Editing using Boundary Sensitivity
36. ICLR 2023Neural Radiance Field Codebooks
37. ICLR 2023NORM: Knowledge Distillation via N-to-One Representation Matching
38. ICLR 2023Omnigrok: Grokking Beyond Algorithmic Data
39. ICLR 2023Out-of-distribution Representation Learning for Time Series Classification
40. ICLR 2023Progressively Compressed Auto-Encoder for Self-supervised Representation Learning
41. ICLR 2023Protein Representation Learning by Geometric Structure Pretraining
42. ICLR 2023Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
43. ICLR 2023Provably Efficient Lifelong Reinforcement Learning with Linear Representation
44. ICLR 2023Relative representations enable zero-shot latent space communication
45. ICLR 2023Reliability of CKA as a Similarity Measure in Deep Learning
46. ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
47. ICLR 2023Self-Supervised Set Representation Learning for Unsupervised Meta-Learning
48. ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
49. ICLR 2023Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning
50. ICLR 2023Spacetime Representation Learning

FAQ

How many Deep learning · representation learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

802 in total: 259 in 2023, 177 in 2024, 152 in 2025, 214 in 2026.

How many Deep learning · representation learning papers are at NeurIPS 2026?

NeurIPS 2026 has 59 Deep learning · representation learning papers, versus 54 the year before.

How many Deep learning · representation learning papers are at ICLR 2026?

ICLR 2026 has 39 Deep learning · representation learning papers, versus 37 the year before.

How many Deep learning · representation learning papers are at ICML 2026?

ICML 2026 has 74 Deep learning · representation learning papers, versus 35 the year before.

How many Deep learning · representation learning papers are at CVPR 2026?

CVPR 2026 has 42 Deep learning · representation learning papers, versus 26 the year before.

Which conference publishes the most Deep learning · representation learning papers?

NeurIPS, with 279 papers from 2023 to 2026.