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

802 papers, page 3 of 17

101. ICML 2026H$^2$CL: Heterogeneity-Aware Hypergraph Contrastive Learning for Robust Representation Learning
102. ICML 2026Hierarchical Goal Abstractions via Learned Subset Relations
103. ICML 2026Hierarchical Successor Representation for Robust Transfer
104. ICML 2026How Should Transformers Encode Numeric Values in Electronic Health Records?
105. ICML 2026Identifiable Equivariant Networks are Layerwise Equivariant
106. ICML 2026INFER: Learning Implicit Neural Frequency Response Fields for Confined Acoustic Environments
107. ICML 2026Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising
108. ICML 2026Joint Learning in the Gaussian Single Index Model
109. ICML 2026Latent Representation Alignment for Offline Goal-Conditioned Reinforcement Learning
110. ICML 2026Learning Global Representation from Queries for Vectorized HD Map Construction
111. ICML 2026Learning High-Frequency Continuous Action Chunks in Latent Space
112. ICML 2026Learning Molecular Semantic Invariant Representation with Prototype Constraint
113. ICML 2026Learning the Minimum Action Distance
114. ICML 2026Learning to Perceive the World Through Control: Empowerment-Based Representation Learning
115. ICML 2026Localized, High-resolution Geographic Representations with Slepian Functions
116. ICML 2026Logit Distance Bounds Representational Similarity
117. ICML 2026Multi-Adapter Representation Interventions via Energy Calibration
118. ICML 2026Multiview Self-Representation Learning across Heterogeneous Views
119. ICML 2026nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
120. ICML 2026Neural Feature Geometry Evolves as Discrete Ricci Flow
121. ICML 2026Nonconvex Low-Rank Tensor Representation with Deep Priors for Multiview Subspace Clustering
122. ICML 2026PatternKV: Flattening KV Representation Expands Quantization Headroom
123. ICML 2026Provable Accuracy Collapse of Embedding-Based Representations under Dimensionality Mismatch
124. ICML 2026QuITE: Query-Based Irregular Time Series Embedding
125. ICML 2026R2R2: Robust Representation for Intensive Experience Reuse via Redundancy Reduction in Self-Predictive Learning
126. ICML 2026Reference-Free Meta-Learning for Generalized Implicit Neural Representation in Efficient MRI Reconstruction
127. ICML 2026Relighting as a Probe of Visual Priors via Augmented Latent Intrinsics
128. ICML 2026Representation Drift Compensation: A Near-Zero Inference Cost Enhancement for LLM Decomposition
129. ICML 2026Representation Learning for Equivariant Inference with Guarantees
130. ICML 2026Representation Unlearning: Forgetting through Information Compression
131. ICML 2026Revisiting the Platonic Representation Hypothesis: An Aristotelian View
132. ICML 2026RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression
133. ICML 2026SABER: Continual Learning with Representation Conflict Management
134. ICML 2026Seeing the Unseen: Physics-as-Representation for Generalizable Gaze Perception
135. ICML 2026Seeking Commonality, Preserving Specificity: A Spectral-Aware Hierarchical Framework for Cross-City Road Representation Learning
136. ICML 2026Separating Representation from Reconstruction Enables Scalable Text Encoders
137. ICML 2026SGERA: Stein-Guided ECG-Report Alignment for ECG Representation Learning
138. ICML 2026Sheaf Neural Networks on SPD Manifolds: Second-Order Geometric Representation Learning
139. ICML 2026SLAE: Strictly Local All-atom Environment for Protein Representation
140. ICML 2026Supervised Graph Contrastive Learning for Gene Regulatory Networks
141. ICML 2026TabularBERT: Binning-Based Self-Supervised Learning for Tabular Representation
142. ICML 2026The Truth Lies Somewhere in the Middle (of the Generated Tokens)
143. ICML 2026Topology-Aware Contrastive Learning: Regulating Representation Connectivity via Persistent Homology
144. ICML 2026Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
145. ICML 2026Uncovering the Latent Potential of Deep Intermediate Representations
146. ICML 2026Understanding Multimodal Learning: A Loss Landscape Smoothness Perspective
147. ICML 2026Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions
148. ICML 2026Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
149. ICML 2026Unsat Core Prediction through Polarity-Aware Representation Learning over Clause-Literal Hypergraphs
150. ICML 2026Variational Learning of Disentangled Representations

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.