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

74 papers, page 2 of 2

51. ICML 2026RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression
52. ICML 2026SABER: Continual Learning with Representation Conflict Management
53. ICML 2026Seeing the Unseen: Physics-as-Representation for Generalizable Gaze Perception
54. ICML 2026Seeking Commonality, Preserving Specificity: A Spectral-Aware Hierarchical Framework for Cross-City Road Representation Learning
55. ICML 2026Separating Representation from Reconstruction Enables Scalable Text Encoders
56. ICML 2026SGERA: Stein-Guided ECG-Report Alignment for ECG Representation Learning
57. ICML 2026Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning
58. ICML 2026SLAE: Strictly Local All-atom Environment for Protein Representation
59. ICML 2026Supervised Graph Contrastive Learning for Gene Regulatory Networks
60. ICML 2026TabularBERT: Binning-Based Self-Supervised Learning for Tabular Representation
61. ICML 2026The Truth Lies Somewhere in the Middle (of the Generated Tokens)
62. ICML 2026Topology-Aware Contrastive Learning: Regulating Representation Connectivity via Persistent Homology
63. ICML 2026Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
64. ICML 2026Uncovering the Latent Potential of Deep Intermediate Representations
65. ICML 2026Understanding Multimodal Learning: A Loss Landscape Smoothness Perspective
66. ICML 2026Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions
67. ICML 2026Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
68. ICML 2026Unsat Core Prediction through Polarity-Aware Representation Learning over Clause-Literal Hypergraphs
69. ICML 2026Variational Learning of Disentangled Representations
70. ICML 2026VBA: Vector Bundle Attention for Intrinsically Geometric Representation Learning
71. ICML 2026Vector Linking via Cross-Model Local Isometric Consistency
72. ICML 2026View Space: Learning Representation across Arbitrary Graphs
73. ICML 2026What Makes a Representation Good for Single-Cell Perturbation Prediction?
74. ICML 2026When Distance Distracts: Representation Distance Bias in BT-Loss for Reward 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.