Deep learning · large language models papers, 2023–2026

Key findings

• Deep learning · large language models went from 488 papers in 2023 to 1,131 in 2026, roughly 2.3x in three years.
• ICML publishes the most Deep learning · large language models work: 1,608 papers from 2023 to 2026, 69% of the four-venue total.
• The fastest-growing overlap is with AI Agents: papers tagged with both rose from 5 in 2023 to 184 in 2026.
• Among the 11 topics under Deep Learning, it ranks #3 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 2.3x here.

Representative papers

Spread across years and venues so every edition shows up

• ICML 2026“very likely” Means “uncertain”? How LLMs Diverge from Humans in Linguistic Uncertainty Quantification
• ICML 2025(How) Do Language Models Track State?
• ICLR 2025AdvWave: Stealthy Adversarial Jailbreak Attack against Large Audio-Language Models
• NeurIPS 2024$\beta$-DPO: Direct Preference Optimization with Dynamic $\beta$
• NeurIPS 20233D-LLM: Injecting the 3D World into Large Language Models
• ICML 2023Are Large Kernels Better Teachers than Transformers for ConvNets?
• ICML 2026$f$-Divergence Self-Play for Tabular Anomaly Detection via Large Language Models
• ICML 2025A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
• ICLR 2025Emergence of a High-Dimensional Abstraction Phase in Language Transformers
• NeurIPS 2024$\textit{Trans-LoRA}$: towards data-free Transferable Parameter Efficient Finetuning
• NeurIPS 2023A fast heuristic to optimize time-space tradeoff for large models
• ICML 2023Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models
• ICML 2026$L^3$: Large Lookup Layers
• ICML 2025Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
• ICLR 2025Holistically Evaluating the Environmental Impact of Creating Language Models
• NeurIPS 2024A distributional simplicity bias in the learning dynamics of transformers
• NeurIPS 2023A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
• ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
• ICML 2026$V_0$: A Generalist Value Model for Any Policy at State Zero
• ICML 2025Accelerating Unbiased LLM Evaluation via Synthetic Feedback

All Deep learning · large language models papers

415 papers, page 4 of 9

151. NeurIPS 2023Global Optimality in Bivariate Gradient-based DAG Learning
152. NeurIPS 2023Goal Driven Discovery of Distributional Differences via Language Descriptions
153. NeurIPS 2023GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction
154. NeurIPS 2023Gradient-Based Feature Learning under Structured Data
155. NeurIPS 2023Grammar Prompting for Domain-Specific Language Generation with Large Language Models
156. NeurIPS 2023GraphAdapter: Tuning Vision-Language Models With Dual Knowledge Graph
157. NeurIPS 2023Grassmann Manifold Flows for Stable Shape Generation
158. NeurIPS 2023Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents
159. NeurIPS 2023Guiding Large Language Models via Directional Stimulus Prompting
160. NeurIPS 2023Guiding The Last Layer in Federated Learning with Pre-Trained Models
161. NeurIPS 2023H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
162. NeurIPS 2023High dimensional, tabular deep learning with an auxiliary knowledge graph
163. NeurIPS 2023High-dimensional Contextual Bandit Problem without Sparsity
164. NeurIPS 2023HIQL: Offline Goal-Conditioned RL with Latent States as Actions
165. NeurIPS 2023HOH: Markerless Multimodal Human-Object-Human Handover Dataset with Large Object Count
166. NeurIPS 2023Horospherical Decision Boundaries for Large Margin Classification in Hyperbolic Space
167. NeurIPS 2023HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection
168. NeurIPS 2023Human spatiotemporal pattern learning as probabilistic program synthesis
169. NeurIPS 2023Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language
170. NeurIPS 2023HyPoradise: An Open Baseline for Generative Speech Recognition with Large Language Models
171. NeurIPS 2023HyTrel: Hypergraph-enhanced Tabular Data Representation Learning
172. NeurIPS 2023IBA: Towards Irreversible Backdoor Attacks in Federated Learning
173. NeurIPS 2023Im-Promptu: In-Context Composition from Image Prompts
174. NeurIPS 2023Image Captioners Are Scalable Vision Learners Too
175. NeurIPS 2023Imagine the Unseen World: A Benchmark for Systematic Generalization in Visual World Models
176. NeurIPS 2023Implicit Variational Inference for High-Dimensional Posteriors
177. NeurIPS 2023Improving Adversarial Transferability via Intermediate-level Perturbation Decay
178. NeurIPS 2023Improving CLIP Training with Language Rewrites
179. NeurIPS 2023Improving Few-Shot Generalization by Exploring and Exploiting Auxiliary Data
180. NeurIPS 2023In-Context Impersonation Reveals Large Language Models' Strengths and Biases
181. NeurIPS 2023In-Context Learning Unlocked for Diffusion Models
182. NeurIPS 2023Inference-Time Intervention: Eliciting Truthful Answers from a Language Model
183. NeurIPS 2023Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives
184. NeurIPS 2023Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
185. NeurIPS 2023Intervention Generalization: A View from Factor Graph Models
186. NeurIPS 2023Intriguing Properties of Quantization at Scale
187. NeurIPS 2023Is Distance Matrix Enough for Geometric Deep Learning?
188. NeurIPS 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
189. NeurIPS 2023KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training
190. NeurIPS 2023Kiki or Bouba? Sound Symbolism in Vision-and-Language Models
191. NeurIPS 2023Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
192. NeurIPS 2023L-CAD: Language-based Colorization with Any-level Descriptions using Diffusion Priors
193. NeurIPS 2023LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark
194. NeurIPS 2023LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
195. NeurIPS 2023Language Is Not All You Need: Aligning Perception with Language Models
196. NeurIPS 2023Language Model Alignment with Elastic Reset
197. NeurIPS 2023Language Model Tokenizers Introduce Unfairness Between Languages
198. NeurIPS 2023Language Models are Weak Learners
199. NeurIPS 2023Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning
200. NeurIPS 2023Language Models can Solve Computer Tasks

FAQ

How many Deep learning · large language models papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,334 in total: 488 in 2023, 298 in 2024, 417 in 2025, 1,131 in 2026.

How many Deep learning · large language models papers are at NeurIPS 2024?

NeurIPS 2024 has 298 Deep learning · large language models papers, versus 415 the year before.

How many Deep learning · large language models papers are at ICLR 2025?

ICLR 2025 has 13 Deep learning · large language models papers.

How many Deep learning · large language models papers are at ICML 2026?

ICML 2026 has 1,131 Deep learning · large language models papers, versus 404 the year before.

Which conference publishes the most Deep learning · large language models papers?

ICML, with 1,608 papers from 2023 to 2026.