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

177 papers, page 3 of 4

101. ICML 2024Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
102. ICML 2024In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
103. ICML 2024Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
104. ICML 2024Learning Graph Representation via Graph Entropy Maximization
105. ICML 2024Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring
106. ICML 2024Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias
107. ICML 2024LLM-Empowered State Representation for Reinforcement Learning
108. ICML 2024Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
109. ICML 2024Polynomial-based Self-Attention for Table Representation Learning
110. ICML 2024Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
111. ICML 2024Position: The Platonic Representation Hypothesis
112. ICML 2024Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains
113. ICML 2024Recurrent Distance Filtering for Graph Representation Learning
114. ICML 2024Rejuvenating image-GPT as Strong Visual Representation Learners
115. ICML 2024RMIB: Representation Matching Information Bottleneck for Matching Text Representations
116. ICML 2024Robustness of Nonlinear Representation Learning
117. ICML 2024SCoRe: Submodular Combinatorial Representation Learning
118. ICML 2024Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
119. ICML 2024TSLANet: Rethinking Transformers for Time Series Representation Learning
120. ICML 2024UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
121. ICML 2024Unsupervised Parameter-free Simplicial Representation Learning with Scattering Transforms
122. ICML 2024Visual Representation Learning with Stochastic Frame Prediction
123. ICML 2024When Representations Align: Universality in Representation Learning Dynamics
124. NeurIPS 2024Aligning Large Language Models with Representation Editing: A Control Perspective
125. NeurIPS 2024AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos
126. NeurIPS 2024Can Transformers Smell Like Humans?
127. NeurIPS 2024Causal Temporal Representation Learning with Nonstationary Sparse Transition
128. NeurIPS 2024CoFie: Learning Compact Neural Surface Representations with Coordinate Fields
129. NeurIPS 2024Conformalized Credal Set Predictors
130. NeurIPS 2024Continuous Heatmap Regression for Pose Estimation via Implicit Neural Representation
131. NeurIPS 2024Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities
132. NeurIPS 2024DenoiseRep: Denoising Model for Representation Learning
133. NeurIPS 2024Diffusion Spectral Representation for Reinforcement Learning
134. NeurIPS 2024Discrete Dictionary-based Decomposition Layer for Structured Representation Learning
135. NeurIPS 2024DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
136. NeurIPS 2024DMesh: A Differentiable Mesh Representation
137. NeurIPS 2024Elliptical Attention
138. NeurIPS 2024Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering
139. NeurIPS 2024Federated Model Heterogeneous Matryoshka Representation Learning
140. NeurIPS 2024Foundations of Multivariate Distributional Reinforcement Learning
141. NeurIPS 2024G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training
142. NeurIPS 2024Generalization Analysis for Label-Specific Representation Learning
143. NeurIPS 2024GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
144. NeurIPS 2024HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
145. NeurIPS 2024HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection
146. NeurIPS 2024Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
147. NeurIPS 2024Improving Gloss-free Sign Language Translation by Reducing Representation Density
148. NeurIPS 2024Latent Functional Maps: a spectral framework for representation alignment
149. NeurIPS 2024Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation
150. NeurIPS 2024Learning diverse causally emergent representations from time series data

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.