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

182 papers, page 1 of 4

1. ICML 2026Action-Sufficient Goal Representations
2. ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
3. ICML 2026Adversarial Robustness of Implicit Neural Representation-Based Classifiers
4. ICML 2026Amortized Maximum Inner Product Search with Learned Support Functions
5. ICML 2026Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning
6. ICML 2026Bridging Functional and Representational Similarity via Usable Information
7. ICML 2026Calibrated Multimodal Representation Learning with Missing Modalities
8. ICML 2026Can Large Language Models Generalize Procedures Across Representations?
9. ICML 2026Cross-Tactile Sensor Representation Learning
10. ICML 2026Deep Ensemble Clustering for Visual Representation Learning
11. ICML 2026Demystifying When Pruning Works via Representation Hierarchies
12. ICML 2026Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
13. ICML 2026From Extrinsic to Intrinsic: Geodesic-Guided Representation Learning for 3D Geometric Data
14. ICML 2026From Generalist to Specialist Representation
15. ICML 2026From Per-Image Low-Rank to Encoding Mismatch: Rethinking Feature Distillation in Vision Transformers
16. ICML 2026Geodesic Calculus on Implicitly Defined Latent Manifolds
17. ICML 2026Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning
18. ICML 2026Grounding Functional Similarity by Invariance-Aware Model Stitching
19. ICML 2026Grouter: Decoupling Routing from Representation for Accelerated MoE Training
20. ICML 2026H$^2$CL: Heterogeneity-Aware Hypergraph Contrastive Learning for Robust Representation Learning
21. ICML 2026Hierarchical Goal Abstractions via Learned Subset Relations
22. ICML 2026Hierarchical Successor Representation for Robust Transfer
23. ICML 2026How Should Transformers Encode Numeric Values in Electronic Health Records?
24. ICML 2026Identifiable Equivariant Networks are Layerwise Equivariant
25. ICML 2026INFER: Learning Implicit Neural Frequency Response Fields for Confined Acoustic Environments
26. ICML 2026Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising
27. ICML 2026Joint Learning in the Gaussian Single Index Model
28. ICML 2026Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
29. ICML 2026Learning Global Representation from Queries for Vectorized HD Map Construction
30. ICML 2026Learning High-Frequency Continuous Action Chunks in Latent Space
31. ICML 2026Learning Molecular Semantic Invariant Representation with Prototype Constraint
32. ICML 2026Learning the Minimum Action Distance
33. ICML 2026Learning to Perceive the World Through Control: Empowerment-Based Representation Learning
34. ICML 2026Localized, High-resolution Geographic Representations with Slepian Functions
35. ICML 2026Logit Distance Bounds Representational Similarity
36. ICML 2026Multi-Adapter Representation Interventions via Energy Calibration
37. ICML 2026Multiview Self-Representation Learning across Heterogeneous Views
38. ICML 2026nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
39. ICML 2026Neural Feature Geometry Evolves as Discrete Ricci Flow
40. ICML 2026Nonconvex Low-Rank Tensor Representation with Deep Priors for Multiview Subspace Clustering
41. ICML 2026PatternKV: Flattening KV Representation Expands Quantization Headroom
42. ICML 2026Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
43. ICML 2026QuITE: Query-Based Irregular Time Series Embedding
44. ICML 2026R2R2: Robust Representation for Intensive Experience Reuse via Redundancy Reduction in Self-Predictive Learning
45. ICML 2026Reference-Free Meta-Learning for Generalized Implicit Neural Representation in Efficient MRI Reconstruction
46. ICML 2026Relighting as a Probe of Visual Priors via Augmented Latent Intrinsics
47. ICML 2026Representation Drift Compensation: A Near-Zero Inference Cost Enhancement for LLM Decomposition
48. ICML 2026Representation Learning for Equivariant Inference with Guarantees
49. ICML 2026Representation Unlearning: Forgetting through Information Compression
50. ICML 2026Revisiting the Platonic Representation Hypothesis: An Aristotelian View

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.