深度学习 · large language models论文趋势 2023–2026

主要结论

• 深度学习 · large language models论文从 2023 年的 488 篇增长到 2026 年的 1,131 篇，三年间扩大到约 2.3 倍。
• ICML 是发深度学习 · large language models论文最多的会议，2023–2026 年共 1,608 篇，占四个会议总量的 69%。
• 交叉方向里涨得最快的是AI 智能体：同时属于两个主题的论文从 2023 年的 5 篇增至 2026 年的 184 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 3；同组增长最快的扩散模型是 4.1 倍，深度学习 · large language models是 2.3 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部深度学习 · large language models论文

共 488 篇，第 4 / 10 页

151. NeurIPS 2023CWCL: Cross-Modal Transfer with Continuously Weighted Contrastive Loss
152. NeurIPS 2023D4: Improving LLM Pretraining via Document De-Duplication and Diversification
153. NeurIPS 2023DAC-DETR: Divide the Attention Layers and Conquer
154. NeurIPS 2023Data Augmentations for Improved (Large) Language Model Generalization
155. NeurIPS 2023Deductive Verification of Chain-of-Thought Reasoning
156. NeurIPS 2023Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration
157. NeurIPS 2023Deep Patch Visual Odometry
158. NeurIPS 2023Deep Stochastic Processes via Functional Markov Transition Operators
159. NeurIPS 2023Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks
160. NeurIPS 2023Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought
161. NeurIPS 2023Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models
162. NeurIPS 2023DesCo: Learning Object Recognition with Rich Language Descriptions
163. NeurIPS 2023Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents
164. NeurIPS 2023Designing Robust Transformers using Robust Kernel Density Estimation
165. NeurIPS 2023Differentiable Random Partition Models
166. NeurIPS 2023Differentially Private Image Classification by Learning Priors from Random Processes
167. NeurIPS 2023DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology
168. NeurIPS 2023DiffUTE: Universal Text Editing Diffusion Model
169. NeurIPS 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Model
170. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
171. NeurIPS 2023Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
172. NeurIPS 2023Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
173. NeurIPS 2023Distributed Inference and Fine-tuning of Large Language Models Over The Internet
174. NeurIPS 2023Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
175. NeurIPS 2023Does Localization Inform Editing? Surprising Differences in Causality-Based Localization vs. Knowledge Editing in Language Models
176. NeurIPS 2023Easy Bayesian Transfer Learning with Informative Priors
177. NeurIPS 2023Efficient Adaptation of Large Vision Transformer via Adapter Re-Composing
178. NeurIPS 2023Efficient Batched Algorithm for Contextual Linear Bandits with Large Action Space via Soft Elimination
179. NeurIPS 2023Efficient Beam Tree Recursion
180. NeurIPS 2023Efficient Diffusion Policies For Offline Reinforcement Learning
181. NeurIPS 2023Efficient Equivariant Transfer Learning from Pretrained Models
182. NeurIPS 2023Efficiently incorporating quintuple interactions into geometric deep learning force fields
183. NeurIPS 2023EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks
184. NeurIPS 2023EMBERSim: A Large-Scale Databank for Boosting Similarity Search in Malware Analysis
185. NeurIPS 2023Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
186. NeurIPS 2023Emergent and Predictable Memorization in Large Language Models
187. NeurIPS 2023EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning
188. NeurIPS 2023Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
189. NeurIPS 2023Epistemic Neural Networks
190. NeurIPS 2023Estimating Koopman operators with sketching to provably learn large scale dynamical systems
191. NeurIPS 2023Evaluating and Inducing Personality in Pre-trained Language Models
192. NeurIPS 2023Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
193. NeurIPS 2023Evaluating Neuron Interpretation Methods of NLP Models
194. NeurIPS 2023Evaluating Open-QA Evaluation
195. NeurIPS 2023Evaluating the Moral Beliefs Encoded in LLMs
196. NeurIPS 2023Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
197. NeurIPS 2023EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
198. NeurIPS 2023EvoPrompting: Language Models for Code-Level Neural Architecture Search
199. NeurIPS 2023Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach
200. NeurIPS 2023Explaining V1 Properties with a Biologically Constrained Deep Learning Architecture

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · large language models论文？

共 2,334 篇，按年份分别是 2023 年 488 篇、2024 年 298 篇、2025 年 417 篇、2026 年 1,131 篇。

NeurIPS 2024 有多少篇深度学习 · large language models论文？

NeurIPS 2024 有 298 篇深度学习 · large language models论文，上一届是 415 篇。

ICLR 2025 有多少篇深度学习 · large language models论文？

ICLR 2025 有 13 篇深度学习 · large language models论文。

ICML 2026 有多少篇深度学习 · large language models论文？

ICML 2026 有 1,131 篇深度学习 · large language models论文，上一届是 404 篇。

哪个会议的深度学习 · large language models论文最多？

ICML，2023–2026 年共 1,608 篇。