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 417 篇，第 1 / 9 页

1. ICLR 2025AdvWave: Stealthy Adversarial Jailbreak Attack against Large Audio-Language Models
2. ICLR 2025Brain-inspired $L_p$-Convolution benefits large kernels and aligns better with visual cortex
3. ICLR 2025DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
4. ICLR 2025Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning
5. ICLR 2025Emergence of a High-Dimensional Abstraction Phase in Language Transformers
6. ICLR 2025Holistically Evaluating the Environmental Impact of Creating Language Models
7. ICLR 2025Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM
8. ICLR 2025Multi-modal brain encoding models for multi-modal stimuli
9. ICLR 2025Personality Alignment of Large Language Models
10. ICLR 2025Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems
11. ICLR 2025Synthetic continued pretraining
12. ICLR 2025Uni-Sign: Toward Unified Sign Language Understanding at Scale
13. ICLR 2025Universal generalization guarantees for Wasserstein distributionally robust models
14. ICML 2025(How) Do Language Models Track State?
15. ICML 2025A Hitchhiker's Guide to Scaling Law Estimation
16. ICML 2025A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
17. ICML 2025A Unified Approach to Routing and Cascading for LLMs
18. ICML 2025Accelerating Large Language Model Reasoning via Speculative Search
19. ICML 2025Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
20. ICML 2025Accelerating Unbiased LLM Evaluation via Synthetic Feedback
21. ICML 2025Active Reward Modeling: Adaptive Preference Labeling for Large Language Model Alignment
22. ICML 2025AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism
23. ICML 2025Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation
24. ICML 2025Adaptive Localization of Knowledge Negation for Continual LLM Unlearning
25. ICML 2025AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
26. ICML 2025Aligning LLMs by Predicting Preferences from User Writing Samples
27. ICML 2025Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models
28. ICML 2025AlphaDPO: Adaptive Reward Margin for Direct Preference Optimization
29. ICML 2025AlphaPO: Reward Shape Matters for LLM Alignment
30. ICML 2025AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and Treefinement
31. ICML 2025AMPO: Active Multi Preference Optimization for Self-play Preference Selection
32. ICML 2025An Analysis for Reasoning Bias of Language Models with Small Initialization
33. ICML 2025An Architecture Search Framework for Inference-Time Techniques
34. ICML 2025An Efficient Pruner for Large Language Model with Theoretical Guarantee
35. ICML 2025An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks
36. ICML 2025Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
37. ICML 2025any4: Learned 4-bit Numeric Representation for LLMs
38. ICML 2025AnyEdit: Edit Any Knowledge Encoded in Language Models
39. ICML 2025Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
40. ICML 2025Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data
41. ICML 2025AuPair: Golden Example Pairs for Code Repair
42. ICML 2025Automated Benchmark Generation for Repository-Level Coding Tasks
43. ICML 2025Automated Hypothesis Validation with Agentic Sequential Falsifications
44. ICML 2025Autonomy-of-Experts Models
45. ICML 2025BackSlash: Rate Constrained Optimized Training of Large Language Models
46. ICML 2025BanditSpec: Adaptive Speculative Decoding via Bandit Algorithms
47. ICML 2025Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective
48. ICML 2025Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
49. ICML 2025BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute
50. ICML 2025Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics

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。