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 1 / 10 页

1. ICML 2023A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models
2. ICML 2023Active Learning based Structural Inference
3. ICML 2023Are Large Kernels Better Teachers than Transformers for ConvNets?
4. ICML 2023Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models
5. ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
6. ICML 2023Bag of Tricks for Training Data Extraction from Language Models
7. ICML 2023Bayes-optimal Learning of Deep Random Networks of Extensive-width
8. ICML 2023Bidirectional Learning for Offline Model-based Biological Sequence Design
9. ICML 2023BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models
10. ICML 2023Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?
11. ICML 2023CataBEEM: Integrating Latent Interaction Categories in Node-wise Community Detection Models for Network Data
12. ICML 2023CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms
13. ICML 2023Compositional Exemplars for In-context Learning
14. ICML 2023Compute-Efficient Deep Learning: Algorithmic Trends and Opportunities
15. ICML 2023ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
16. ICML 2023Controlled Text Generation with Natural Language Instructions
17. ICML 2023Cramming: Training a Language Model on a single GPU in one day.
18. ICML 2023DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design
19. ICML 2023Deep linear networks can benignly overfit when shallow ones do
20. ICML 2023Differentially Private Optimization on Large Model at Small Cost
21. ICML 2023Distilling Internet-Scale Vision-Language Models into Embodied Agents
22. ICML 2023Do Machine Learning Models Learn Statistical Rules Inferred from Data?
23. ICML 2023Doubly Optimal No-Regret Learning in Monotone Games
24. ICML 2023Dropout Reduces Underfitting
25. ICML 2023Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation
26. ICML 2023FedVS: Straggler-Resilient and Privacy-Preserving Vertical Federated Learning for Split Models
27. ICML 2023FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization
28. ICML 2023Grounding Language Models to Images for Multimodal Inputs and Outputs
29. ICML 2023Guiding Pretraining in Reinforcement Learning with Large Language Models
30. ICML 2023Hindsight Learning for MDPs with Exogenous Inputs
31. ICML 2023Hyena Hierarchy: Towards Larger Convolutional Language Models
32. ICML 2023Identifying Interpretable Subspaces in Image Representations
33. ICML 2023ILLUME: Rationalizing Vision-Language Models through Human Interactions
34. ICML 2023Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models
35. ICML 2023Instant Soup: Cheap Pruning Ensembles in A Single Pass Can Draw Lottery Tickets from Large Models
36. ICML 2023Language Instructed Reinforcement Learning for Human-AI Coordination
37. ICML 2023Large Language Models Can Be Easily Distracted by Irrelevant Context
38. ICML 2023Learning Hidden Markov Models When the Locations of Missing Observations are Unknown
39. ICML 2023Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments
40. ICML 2023Learning Unnormalized Statistical Models via Compositional Optimization
41. ICML 2023Learning-augmented private algorithms for multiple quantile release
42. ICML 2023Learning-Rate-Free Learning by D-Adaptation
43. ICML 2023Less is More: Task-aware Layer-wise Distillation for Language Model Compression
44. ICML 2023LEVER: Learning to Verify Language-to-Code Generation with Execution
45. ICML 2023LongCoder: A Long-Range Pre-trained Language Model for Code Completion
46. ICML 2023MALTS: Matching After Learning to Stretch
47. ICML 2023Maximal Initial Learning Rates in Deep ReLU Networks
48. ICML 2023Minimal Width for Universal Property of Deep RNN
49. ICML 2023OCD: Learning to Overfit with Conditional Diffusion Models
50. ICML 2023One-Shot Compression of Large Edge-Exchangeable Graphs using Bits-Back Coding

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。