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

59 papers, page 1 of 2

1. NeurIPS 2026A Unified Uncertainty Representation for Graph Neural Networks via Doubly-Spectral Stochastic Expansion
2. NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
3. NeurIPS 2026Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation
4. NeurIPS 2026AnchorRep: Defending LLMs Against Cross-Model Adversarial Transfer via Representation Repulsion
5. NeurIPS 2026Approximation in Contrastive Representation Learning
6. NeurIPS 2026Biological Graph Priors Enable Representation Learning for Cellular Microscopy
7. NeurIPS 2026Boosting Graph Contrastive Learning via Manifold-Guided Representation Disentanglement
8. NeurIPS 2026Class–Domain Discriminability Guided Representation Enhancement for Domain Generalization
9. NeurIPS 2026Closed-Form Implicit Neural Representations
10. NeurIPS 2026Contrastive Representation Shaping for LLM Unlearning
11. NeurIPS 2026CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers
12. NeurIPS 2026Deadline-Constrained Dynamic Workflow Scheduling Can be Cast as a Representation Learning Problem
13. NeurIPS 2026Decentralized Coupled Representation Learning
14. NeurIPS 2026DiffRisk: Diffusion Representation Learning with Informative Missingness for Health Risk Prediction
15. NeurIPS 2026Disentangled Representation Learning via Flow Matching
16. NeurIPS 2026dRAE: Representation Autoencoder with Hyper-Spherical Codes
17. NeurIPS 2026Dynamic Representation Modeling for Federated Medical Image Domain Generalization
18. NeurIPS 2026Energy-Adaptive Equivariant State Space Models for Noise-Robust Protein Structure Representation
19. NeurIPS 2026Escaping Parameter Space: Tight Generalization Bounds via Representation Quality
20. NeurIPS 2026Finding Koopman Invariant Subspaces via Personalized PageRank
21. NeurIPS 2026FuncFormer: Circuit Representation Learning via the Flow of Functional Propagation
22. NeurIPS 2026GaitLingo: Self-Supervised Gait Representation Learning with Language Priors
23. NeurIPS 2026GEM: A Dual-Scale Architecture for Graph-Level Hierarchical Representation Learning
24. NeurIPS 2026Geometry-Aware Self-Supervised Electrophysiology Representation Learning
25. NeurIPS 2026GIFT: Representation Geometry Matters for Single-Domain Generalized Object Detection
26. NeurIPS 2026Hadamard Representation: Scaffolding Performance Across Model-free RL
27. NeurIPS 2026Harder the Task, Sparser the Representation: Sparsity as a Learning Signature of Capability in LLMs
28. NeurIPS 2026Hierarchical Graph Representation Learning with Pooling-Induced Substructures
29. NeurIPS 2026HiLoc: A Hierarchical Representation Method for Spatial Localization in Multimodal Large Language Models
30. NeurIPS 2026How Do Language Models Compose Functions?
31. NeurIPS 2026Hypergraph Representation Learning with Hyperlink Random Effects
32. NeurIPS 2026Intrinsic Information Theoretic Analysis of ReLU Nets
33. NeurIPS 2026Is a Linear Probe Evidence of a Linear Representation?
34. NeurIPS 2026KINDER: Kernel-based Independence for Fair Representation Learning via Prototype-space Erasure
35. NeurIPS 2026Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis
36. NeurIPS 2026LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift
37. NeurIPS 2026MCM-DM: Towards Better Spatio-Temporal Event Representation Learning via Discrete Morse Theory
38. NeurIPS 2026Mind the Heads: Topological Representation Alignment for Multimodal LLMs
39. NeurIPS 2026MinSteer: Minimal-Pair Steering via Two-Stage Cached Continuation
40. NeurIPS 2026MIRAGE: Duality-Inspired MILP Augmentation for Representation Learning
41. NeurIPS 2026MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data
42. NeurIPS 2026Neural-Behavioral Representation of Natural Whole-body Movement in Monkeys
43. NeurIPS 2026NIKA: Efficient Neural Video Representation via Structured Latent Diversity
44. NeurIPS 2026NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling
45. NeurIPS 2026One Unified Representation: Resolving the Appearance-Semantics Dilemma via Structural Regularization
46. NeurIPS 2026Oversmoothing as Representation Degeneracy in Neural Sheaf Diffusion
47. NeurIPS 2026Predictive Representation Learning for Partially Observed Neural Dynamics
48. NeurIPS 2026Primal-Dual Representation Learning for Low-Rank Constrained MDPs
49. NeurIPS 2026Provably Efficient Representation Learning for Low-Rank CMDPs
50. NeurIPS 2026Representation Forcing for Bottleneck-Free Unified Multimodal Models

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.