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

279 papers, page 3 of 6

101. NeurIPS 2025Temporal Representation Alignment: Successor Features Enable Emergent Compositionality in Robot Instruction Following
102. NeurIPS 2025The Indra Representation Hypothesis
103. NeurIPS 2025Theory-Driven Label-Specific Representation for Incomplete Multi-View Multi-Label Learning
104. NeurIPS 2025Token Bottleneck: One Token to Remember Dynamics
105. NeurIPS 2025TopER: Topological Embeddings in Graph Representation Learning
106. NeurIPS 2025Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies
107. NeurIPS 2025Towards Implicit Aggregation: Robust Image Representation for Place Recognition in the Transformer Era
108. NeurIPS 2025Tracing the Representation Geometry of Language Models from Pretraining to Post-training
109. NeurIPS 2025U-REPA: Aligning Diffusion U-Nets to ViTs
110. NeurIPS 2025VA-GS: Enhancing the Geometric Representation of Gaussian Splatting via View Alignment
111. NeurIPS 2025VQToken: Neural Discrete Token Representation Learning for Extreme Token Reduction in Video Large Language Models
112. NeurIPS 2025When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective
113. NeurIPS 2025X-Field: A Physically Informed Representation for 3D X-ray Reconstruction
114. NeurIPS 2024Aligning Large Language Models with Representation Editing: A Control Perspective
115. NeurIPS 2024AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos
116. NeurIPS 2024Can Transformers Smell Like Humans?
117. NeurIPS 2024Causal Temporal Representation Learning with Nonstationary Sparse Transition
118. NeurIPS 2024CoFie: Learning Compact Neural Surface Representations with Coordinate Fields
119. NeurIPS 2024Conformalized Credal Set Predictors
120. NeurIPS 2024Continuous Heatmap Regression for Pose Estimation via Implicit Neural Representation
121. NeurIPS 2024Contrasting with Symile: Simple Model-Agnostic Representation Learning for Unlimited Modalities
122. NeurIPS 2024DenoiseRep: Denoising Model for Representation Learning
123. NeurIPS 2024Diffusion Spectral Representation for Reinforcement Learning
124. NeurIPS 2024Discrete Dictionary-based Decomposition Layer for Structured Representation Learning
125. NeurIPS 2024DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
126. NeurIPS 2024DMesh: A Differentiable Mesh Representation
127. NeurIPS 2024Elliptical Attention
128. NeurIPS 2024Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering
129. NeurIPS 2024Federated Model Heterogeneous Matryoshka Representation Learning
130. NeurIPS 2024Foundations of Multivariate Distributional Reinforcement Learning
131. NeurIPS 2024G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training
132. NeurIPS 2024Generalization Analysis for Label-Specific Representation Learning
133. NeurIPS 2024GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
134. NeurIPS 2024HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning
135. NeurIPS 2024HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection
136. NeurIPS 2024Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
137. NeurIPS 2024Improving Gloss-free Sign Language Translation by Reducing Representation Density
138. NeurIPS 2024Latent Functional Maps: a spectral framework for representation alignment
139. NeurIPS 2024Learning 3D Equivariant Implicit Function with Patch-Level Pose-Invariant Representation
140. NeurIPS 2024Learning diverse causally emergent representations from time series data
141. NeurIPS 2024Learning on Large Graphs using Intersecting Communities
142. NeurIPS 2024Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation
143. NeurIPS 2024Learning Structured Representations with Hyperbolic Embeddings
144. NeurIPS 2024Leveraging Tumor Heterogeneity: Heterogeneous Graph Representation Learning for Cancer Survival Prediction in Whole Slide Images
145. NeurIPS 2024LinNet: Linear Network for Efficient Point Cloud Representation Learning
146. NeurIPS 2024MatrixNet: Learning over symmetry groups using learned group representations
147. NeurIPS 2024Neural Isometries: Taming Transformations for Equivariant ML
148. NeurIPS 2024NeuRodin: A Two-stage Framework for High-Fidelity Neural Surface Reconstruction
149. NeurIPS 2024Not All Diffusion Model Activations Have Been Evaluated as Discriminative Features
150. NeurIPS 2024NVRC: Neural Video Representation Compression

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.