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

259 papers, page 3 of 6

101. ICLR 2023Provably Efficient Lifelong Reinforcement Learning with Linear Representation
102. ICLR 2023Relative representations enable zero-shot latent space communication
103. ICLR 2023Reliability of CKA as a Similarity Measure in Deep Learning
104. ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
105. ICLR 2023Self-Supervised Set Representation Learning for Unsupervised Meta-Learning
106. ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
107. ICLR 2023Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning
108. ICLR 2023Spacetime Representation Learning
109. ICLR 2023Spectral Decomposition Representation for Reinforcement Learning
110. ICLR 2023Task-Aware Information Routing from Common Representation Space in Lifelong Learning
111. ICLR 2023The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks
112. ICLR 2023Time to augment self-supervised visual representation learning
113. ICLR 2023Toward Adversarial Training on Contextualized Language Representation
114. ICLR 2023Uni-Mol: A Universal 3D Molecular Representation Learning Framework
115. ICLR 2023Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning
116. ICLR 2023Weighted Ensemble Self-Supervised Learning
117. ICML 2023A General Representation Learning Framework with Generalization Performance Guarantees
118. ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
119. ICML 2023Adversarial Collaborative Learning on Non-IID Features
120. ICML 2023Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
121. ICML 2023Deep Graph Representation Learning and Optimization for Influence Maximization
122. ICML 2023Defects of Convolutional Decoder Networks in Frequency Representation
123. ICML 2023Diffusion Based Representation Learning
124. ICML 2023Disentangled Multiplex Graph Representation Learning
125. ICML 2023Dynamics-inspired Neuromorphic Visual Representation Learning
126. ICML 2023Entropy-driven Unsupervised Keypoint Representation Learning in Videos
127. ICML 2023FARE: Provably Fair Representation Learning with Practical Certificates
128. ICML 2023Feature Directions Matter: Long-Tailed Learning via Rotated Balanced Representation
129. ICML 2023FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization
130. ICML 2023Generalization Analysis for Contrastive Representation Learning
131. ICML 2023Hyperbolic Representation Learning: Revisiting and Advancing
132. ICML 2023InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models
133. ICML 2023Internet Explorer: Targeted Representation Learning on the Open Web
134. ICML 2023Interventional Causal Representation Learning
135. ICML 2023Learning Affinity with Hyperbolic Representation for Spatial Propagation
136. ICML 2023Multi-task Representation Learning for Pure Exploration in Linear Bandits
137. ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
138. ICML 2023Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
139. ICML 2023Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
140. ICML 2023Representation-Driven Reinforcement Learning
141. ICML 2023Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition
142. ICML 2023Stochastic Gradient Descent-Induced Drift of Representation in a Two-Layer Neural Network
143. ICML 2023The Numerical Stability of Hyperbolic Representation Learning
144. ICML 2023Tied-Augment: Controlling Representation Similarity Improves Data Augmentation
145. ICML 2023Towards a better understanding of representation dynamics under TD-learning
146. ICML 2023Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering
147. ICML 2023Weakly Supervised Disentangled Generative Causal Representation Learning
148. NeurIPS 2023[Re] CrossWalk: Fairness-enhanced Node Representation Learning
149. NeurIPS 2023$\texttt{TACO}$: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
150. NeurIPS 2023A Hierarchical Spatial Transformer for Massive Point Samples in Continuous Space

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.