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

112 papers, page 1 of 3

1. NeurIPS 2023[Re] CrossWalk: Fairness-enhanced Node Representation Learning
2. NeurIPS 2023$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
3. NeurIPS 2023A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space
4. NeurIPS 2023A State Representation for Diminishing Rewards
5. NeurIPS 2023Achieving Cross Modal Generalization with Multimodal Unified Representation
6. NeurIPS 2023Active representation learning for general task space with applications in robotics
7. NeurIPS 2023AdANNS: A Framework for Adaptive Semantic Search
8. NeurIPS 2023CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
9. NeurIPS 2023CAT-Walk: Inductive Hypergraph Learning via Set Walks
10. NeurIPS 2023CL-NeRF: Continual Learning of Neural Radiance Fields for Evolving Scene Representation
11. NeurIPS 2023Combating Representation Learning Disparity with Geometric Harmonization
12. NeurIPS 2023Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
13. NeurIPS 2023Connecting Multi-modal Contrastive Representations
14. NeurIPS 2023Connecting Pre-trained Language Model and Downstream Task via Properties of Representation
15. NeurIPS 2023Counterfactually Fair Representation
16. NeurIPS 2023Data-Informed Geometric Space Selection
17. NeurIPS 2023Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
18. NeurIPS 2023Deep Non-line-of-sight Imaging from Under-scanning Measurements
19. NeurIPS 2023Differentiable Clustering with Perturbed Spanning Forests
20. NeurIPS 2023Diffused Redundancy in Pre-trained Representations
21. NeurIPS 2023Diffusion Representation for Asymmetric Kernels via Magnetic Transform
22. NeurIPS 2023Directional diffusion models for graph representation learning
23. NeurIPS 2023Disentangling Cognitive Diagnosis with Limited Exercise Labels
24. NeurIPS 2023DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions
25. NeurIPS 2023DrugCLIP: Contrastive Protein-Molecule Representation Learning for Virtual Screening
26. NeurIPS 2023Dynamic Tensor Decomposition via Neural Diffusion-Reaction Processes
27. NeurIPS 2023E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning
28. NeurIPS 2023Eliminating Domain Bias for Federated Learning in Representation Space
29. NeurIPS 2023Emergent Communication for Rules Reasoning
30. NeurIPS 2023EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning
31. NeurIPS 2023Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns
32. NeurIPS 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
33. NeurIPS 2023Feature Selection in the Contrastive Analysis Setting
34. NeurIPS 2023Flow Factorized Representation Learning
35. NeurIPS 2023FLSL: Feature-level Self-supervised Learning
36. NeurIPS 2023For SALE: State-Action Representation Learning for Deep Reinforcement Learning
37. NeurIPS 2023FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow
38. NeurIPS 2023Full-Atom Protein Pocket Design via Iterative Refinement
39. NeurIPS 2023Fundamental Limits and Tradeoffs in Invariant Representation Learning
40. NeurIPS 2023Going beyond persistent homology using persistent homology
41. NeurIPS 2023Guide Your Agent with Adaptive Multimodal Rewards
42. NeurIPS 2023HiNeRV: Video Compression with Hierarchical Encoding-based Neural Representation
43. NeurIPS 2023How hard are computer vision datasets? Calibrating dataset difficulty to viewing time
44. NeurIPS 2023Hyperbolic VAE via Latent Gaussian Distributions
45. NeurIPS 2023HyTrel: Hypergraph-enhanced Tabular Data Representation Learning
46. NeurIPS 2023Identifiable Contrastive Learning with Automatic Feature Importance Discovery
47. NeurIPS 2023Ignorance is Bliss: Robust Control via Information Gating
48. NeurIPS 2023Implicit Contrastive Representation Learning with Guided Stop-gradient
49. NeurIPS 2023Improving neural network representations using human similarity judgments
50. NeurIPS 2023Intensity Profile Projection: A Framework for Continuous-Time Representation Learning for Dynamic Networks

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.